03_image_processing/06_Image_Filters.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "af62c119-71c5-4047-9451-28d5fb42f566",
   "metadata": {},
   "source": [
    "# Image Processing Filters"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a821ebf-e246-4b22-8a8e-97b05dcc1150",
   "metadata": {},
   "source": [
    "Filters are mathematical operations that produce a new image out of one or more images. Pixel values between input and output images may differ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c5b49ac1-5496-4201-8bf6-a134a8de2998",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from skimage.io import imread\n",
    "from skimage import data\n",
    "from skimage import filters\n",
    "from skimage import morphology\n",
    "from scipy.ndimage import convolve, gaussian_laplace\n",
    "import stackview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bf1f395-6ec3-4679-9633-69d221d12440",
   "metadata": {},
   "source": [
    "To demonstrate what specific filters do, we start with a very simple image. It contains a lot of zeros and a single pixel with value `1` in the middle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "dea7213b-e0b4-44d8-956f-9ef95613741e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0.],\n",
       "       [0., 0., 1., 0., 0.],\n",
       "       [0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0.]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image1 = np.zeros((5, 5))\n",
    "image1[2, 2] = 1\n",
    "image1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0656b0e1-24e8-4dcd-9e68-6aa603c587a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x1d867e926d0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(image1, cmap='gray')\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d69a61c0-c875-4da2-a809-dce5055ee572",
   "metadata": {},
   "source": [
    "## Gaussian kernel\n",
    "To apply a _Gaussian blur_ to an image, we convolve it using a Gaussian kernel. The function [`gaussian` in scikit-image](https://scikit-image.org/docs/stable/api/skimage.filters.html#skimage.filters.gaussian) can do this for us."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "236fe675-7af1-4b6b-a781-8c58cf57e4f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.00291504, 0.01306431, 0.02153941, 0.01306431, 0.00291504],\n",
       "       [0.01306431, 0.05855018, 0.09653293, 0.05855018, 0.01306431],\n",
       "       [0.02153941, 0.09653293, 0.15915589, 0.09653293, 0.02153941],\n",
       "       [0.01306431, 0.05855018, 0.09653293, 0.05855018, 0.01306431],\n",
       "       [0.00291504, 0.01306431, 0.02153941, 0.01306431, 0.00291504]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blurred = filters.gaussian(image1, sigma=1)\n",
    "blurred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8109c64a-756d-4e1d-8e10-52e797965625",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x1d867f459d0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(blurred, cmap='gray')\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ebfa6c4-b027-4e6c-a12a-c502ecdd923c",
   "metadata": {},
   "source": [
    "## Laplacian\n",
    "Whenever you wonder what a filter might be doing, just create a simple test image and apply the filter to it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "662a5af6-36ce-4c62-b751-2358dca60fe6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x1d86801abe0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "image2 = np.zeros((9, 9))\n",
    "image2[4, 4] = 1\n",
    "\n",
    "plt.imshow(image2, cmap='gray')\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2c57c338-18f8-4347-801a-6f4bf1d680ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x1d868707b50>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeEAAAGiCAYAAADQhn7MAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAglklEQVR4nO3df2xV9f3H8Vet6y0/eq8CttJwgToX+VEQbIlrQcWJTSoSSRz+CDL8lQwpSG1msOIEmXh1341gZFRLCOIMliyKskzQ6oTKsLMUqkwNuEnsnVIZTu+FGm/D5X7/2Jf73S0UuL/6Obef5yM5f9yTc8/n3Zvoi/f7nHtPViQSiQgAAPS680wXAACArQhhAAAMIYQBADCEEAYAwBBCGAAAQwhhAAAMIYQBADCEEAYAwBBCGAAAQwhhAAAMIYQBADgNn8+nrKwsVVdXp20NQhgAgG5aWlpUX1+v8ePHp3UdQhgAgP9y7NgxzZ49W2vXrtWFF16Y1rXOT+vZT+PEiRP68ssvlZeXp6ysrN5eHgCQhEgkoqNHj6qwsFDnnZe+Pu77779XV1dX0ueJRCKnZI3L5ZLL5erxPVVVVZo+fbqmTZumxx9/POkazqTXQ/jLL7+U1+vt7WUBACnk9/s1bNiwtJz7+++/V1FRkTo6OpI+18CBA3Xs2LGYfUuXLtWyZctOe3xDQ4P27NmjlpaWpNc+F70ewnl5eZKkcePGKTs7u7eXBwAkIRwOa9++fdH/l6dDV1eXOjo61N7eLrfbnfB5gsGghg8fLr/fH3Oenrpgv9+vRYsW6c0331Rubm7C68aj10P45FggOzubEAaADNUblxPdbndSIRzveVpbW3X48GGVlJRE94XDYTU1NWn16tUKhUIpz61eD2EAAM5FJBJRJBJJ6v3xuO6667Rv376YfXfddZdGjRqlxYsXp6VxJIQBAI7U2yGcl5en4uLimH0DBgzQ4MGDT9mfKoQwAMCRejuETSCEAQDowfbt29N6fkIYAOBIdMIAABhiQwjzs5UAABhCJwwAcCQbOmFCGADgSDaEMONoAAAMoRMGADiSDZ0wIQwAcCQbQphxNAAAhtAJAwAciU64B2vWrFFRUZFyc3NVUlKid999N9V1AQAsdzKEk9mcLu4Q3rRpk6qrq7VkyRLt3btXV111lSorK9Xe3p6O+gAAliKET2PlypW65557dO+992r06NFatWqVvF6v6urqTnt8KBRSMBiM2QAAQJwh3NXVpdbWVlVUVMTsr6io0K5du077Hp/PJ4/HE928Xm/i1QIArEEn3M2RI0cUDodVUFAQs7+goEAdHR2nfU9tba0CgUB08/v9iVcLALCGDSGc0N3RWVlZMa8jkcgp+05yuVxyuVyJLAMAQJ8WVwgPGTJE2dnZp3S9hw8fPqU7BgAgGXxFqZucnByVlJSosbExZn9jY6PKy8tTWhgAwG6Mo0+jpqZGc+bMUWlpqcrKylRfX6/29nbNmzcvHfUBANBnxR3Ct956q77++mstX75chw4dUnFxsV5//XWNGDEiHfUBACxlwzg6oRuz5s+fr/nz56e6FgAAYmRCkCaDBzgAAGAID3AAADgS42gAAAwhhAEAMMSGEOaaMAAAhtAJAwAcyYZOmBAGADiSDSHMOBoAAEPohAEAjmRDJ0wIAwAcyYYQZhwNAIAhdMIAAEeyoRMmhAEAjmRDCDOOBgDAEDphAIAj2dAJE8IAAEcihAEAMMSGEOaaMAAAhtAJAwAcyYZOmBAGADiSDSHMOBoAAEPohAEAjmRDJ0wIAwAcyYYQZhwNAIAhdMIAAEeyoRMmhAEAjpUJQZoMxtEAABhCJwwAcCTG0QAAGEIIAwBgiA0hHPc14aamJs2YMUOFhYXKysrSq6++moayAADo++IO4c7OTl1++eVavXp1OuoBAEDS/3fCyWxOF/c4urKyUpWVled8fCgUUigUir4OBoPxLgkAsBDj6BTw+XzyeDzRzev1pntJAAAyQtpDuLa2VoFAILr5/f50LwkA6AMYR6eAy+WSy+VK9zIAgD6GcTQAAEgbvicMAHAkGzrhuEP42LFj+vvf/x59ffDgQbW1tWnQoEEaPnx4SosDANiLED6N3bt369prr42+rqmpkSTNnTtXzz//fMoKAwCgr4s7hKdOnZoR/7oAAGQ2OmEAAAyxIYS5OxoA4Ei9/T3huro6jR8/Xm63W263W2VlZdq6dWua/rr/IIQBAJA0bNgwPfnkk9q9e7d2796tn/zkJ7rpppv00UcfpW1NxtEAAEfq7XH0jBkzYl6vWLFCdXV1am5u1tixYxOu40wIYQCAI6UqhLs/OOhcfskxHA7rD3/4gzo7O1VWVpZwDWfDOBoA0Kd5vd6YBwn5fL4ej923b58GDhwol8ulefPmafPmzRozZkzaaqMTBgA4Uqo6Yb/fL7fbHd1/pi74sssuU1tbm7799lu9/PLLmjt3rnbs2JG2ICaEAQCOlKoQPnm387nIycnRpZdeKkkqLS1VS0uLnn76aT333HMJ13EmjKMBAOhBJBJRKBRK2/nphAEAjtTbd0c//PDDqqyslNfr1dGjR9XQ0KDt27dr27ZtCddwNoQwAMCxevNXr7766ivNmTNHhw4dksfj0fjx47Vt2zZdf/31aVuTEAYAQNK6det6fU1CGADgSDb8djQhDABwJEIYAABDbAhhvqIEAIAhdMIAAEeyoRMmhAEAjmRDCDOOBgDAEDphAIAj2dAJE8IAAEeyIYQZRwMAYAidMADAkWzohAlhAIAj2RDCjKMBADCEThgA4Eg2dMKEMADAkQhhAAAMsSGEuSYMAIAhdMIAAEeiE+7G5/Np0qRJysvLU35+vmbOnKn9+/enqzYAgMVOhnAym9PFFcI7duxQVVWVmpub1djYqOPHj6uiokKdnZ3pqg8AgD4rrnH0tm3bYl6vX79e+fn5am1t1dVXX33a94RCIYVCoejrYDCYQJkAANswjj6LQCAgSRo0aFCPx/h8Pnk8nujm9XqTWRIAYAnG0WcQiURUU1OjKVOmqLi4uMfjamtrFQgEopvf7090SQAA+pSE745esGCBPvzwQ+3cufOMx7lcLrlcrkSXAQBYyoZxdEIhvHDhQm3ZskVNTU0aNmxYqmsCAEBSZgRpMuIK4UgkooULF2rz5s3avn27ioqK0lUXAAB9XlwhXFVVpY0bN+q1115TXl6eOjo6JEkej0f9+vVLS4EAADvZMI6O68asuro6BQIBTZ06VUOHDo1umzZtSld9AABL2XB3dNzjaAAAegOdMAAASBse4AAAcCQbOmFCGADgSDaEMONoAAAMoRMGADiSDZ0wIQwAcCQbQphxNAAAhtAJAwAcyYZOmBAGADiSDSHMOBoAAEPohAEAjmRDJ0wIAwAciRAGLNDa2mq6hHNSUlJiugSgV9kQwlwTBgDAEDphAIAj2dAJE8IAAEeyIYQZRwMAYAidMADAkWzohAlhAIAj2RDCjKMBADCEThgA4Eg2dMKEMADAkWwIYcbRAAAYQicMAHCsTOhmk0EIAwAcyYZxNCEMAHAkG0KYa8IAABhCJwwAcCQbOmFCGADgSDaEMONoAAAMiSuE6+rqNH78eLndbrndbpWVlWnr1q3pqg0AYLGTnXAym9PFNY4eNmyYnnzySV166aWSpA0bNuimm27S3r17NXbs2LQUCACwkw3j6LhCeMaMGTGvV6xYobq6OjU3N/cYwqFQSKFQKPo6GAwmUCYAAH1PwteEw+GwGhoa1NnZqbKysh6P8/l88ng80c3r9Sa6JADAIjaMo+MO4X379mngwIFyuVyaN2+eNm/erDFjxvR4fG1trQKBQHTz+/1JFQwAsENvh7DP59OkSZOUl5en/Px8zZw5U/v370/TX/cfcYfwZZddpra2NjU3N+u+++7T3Llz9fHHH/d4vMvlit7IdXIDAOBsejuEd+zYoaqqKjU3N6uxsVHHjx9XRUWFOjs70/QXJvA94ZycnOiNWaWlpWppadHTTz+t5557LuXFAQDQW7Zt2xbzev369crPz1dra6uuvvrqtKyZ9I91RCKRmBuvAABIhVTdHd39hmCXyyWXy3XW9wcCAUnSoEGDEq7hbOIK4YcffliVlZXyer06evSoGhoatH379lP+9QAAQLJSFcLdbwheunSpli1bdtb31tTUaMqUKSouLk64hrOJK4S/+uorzZkzR4cOHZLH49H48eO1bds2XX/99emqDwCApPj9/pj7kc6lC16wYIE+/PBD7dy5M52lxRfC69atS1cdAADESFUnHO9NwQsXLtSWLVvU1NSkYcOGJbz+ueABDgAAR+rtX8yKRCJauHChNm/erO3bt6uoqCjhtc8VIQwAgKSqqipt3LhRr732mvLy8tTR0SFJ8ng86tevX1rW5ClKAABH6u3vCdfV1SkQCGjq1KkaOnRodNu0aVOa/kI6YQCAQ5kYR/c2OmEAAAyhEwYAOBKPMgQAwBBCGAAAgzIhSJPBNWEAAAyhEwYAOBLjaAAADLEhhBlHAwBgCJ0w0qq1tdV0CWeVCf9alqSsrCzTJZxVSUmJ6RLQh9jQCRPCAABHsiGEGUcDAGAInTAAwJFs6IQJYQCAI9kQwoyjAQAwhE4YAOBINnTChDAAwJEIYQAADLEhhLkmDACAIXTCAABHsqETJoQBAI5kQwgzjgYAwBA6YQCAI9nQCRPCAABHsiGEGUcDAGAInTAAwJFs6IQJYQCAI9kQwkmNo30+n7KyslRdXZ2icgAAsEfCnXBLS4vq6+s1fvz4VNYDAIAkOuEeHTt2TLNnz9batWt14YUXnvHYUCikYDAYswEAcDYnQziZzekSCuGqqipNnz5d06ZNO+uxPp9PHo8nunm93kSWBABYqC8HsJRACDc0NGjPnj3y+XzndHxtba0CgUB08/v9cRcJAEBfFNc1Yb/fr0WLFunNN99Ubm7uOb3H5XLJ5XIlVBwAwF42XBOOK4RbW1t1+PBhlZSURPeFw2E1NTVp9erVCoVCys7OTnmRAAD7EMLdXHfdddq3b1/MvrvuukujRo3S4sWLCWAAAOIQVwjn5eWpuLg4Zt+AAQM0ePDgU/YDAJAMOmEAAAwhhM/B9u3bU1AGAAD2oRMGADgSnTAAAIbYEMI8TxgAAEPohAEAjmRDJ0wIAwAciRAGAMAQG0KYa8IAABhCJwwAcCQbOmFCGADgSDaEMONoAAAMoRMGADiSDZ0wIQwAcCRCGEhSSUmJ6RLOKisry3QJ5yQTPksA8SGEAQCORCcMAIAhNoQwd0cDAGAInTAAwJFs6IQJYQCAIxHCAAAYlAlBmgyuCQMAYAidMADAkRhHAwBgiA0hzDgaAABD6IQBAI5kQydMCAMAHMmGEGYcDQCAIYQwAMCRTnbCyWzxampq0owZM1RYWKisrCy9+uqrqf/D/gshDABwJBMh3NnZqcsvv1yrV69Ow190Kq4JAwD6tGAwGPPa5XLJ5XKd9tjKykpVVlb2RlmS6IQBAA6Vqk7Y6/XK4/FEN5/PZ/gv+39xdcLLli3TY489FrOvoKBAHR0dKS0KAIBU3R3t9/vldruj+3vqgk2Iexw9duxYvfXWW9HX2dnZKS0IAAApdSHsdrtjQthJ4g7h888/XxdffHE6agEAwCpxXxP+9NNPVVhYqKKiIt1222367LPPznh8KBRSMBiM2QAAOBsTd0f3trhC+Morr9QLL7ygN954Q2vXrlVHR4fKy8v19ddf9/gen88Xc0Hc6/UmXTQAoO8zEcLHjh1TW1ub2traJEkHDx5UW1ub2tvbU/zX/UdcIVxZWambb75Z48aN07Rp0/SnP/1JkrRhw4Ye31NbW6tAIBDd/H5/chUDAJAmu3fv1sSJEzVx4kRJUk1NjSZOnKhHH300Lesl9T3hAQMGaNy4cfr00097POZM38cCAKAnJn47eurUqb06xk7qe8KhUEiffPKJhg4dmqp6AACQxDXhU/ziF7/Qjh07dPDgQf31r3/VT3/6UwWDQc2dOzdd9QEA0GfFNY7+5z//qdtvv11HjhzRRRddpB//+Mdqbm7WiBEj0lUfAMBSNjzKMK4QbmhoSFcdAADEsCGE+e1oAAAM4SlKAABHsqETJoQBAI5ECAMAYFAmBGkyuCYMAIAhdMIAAEdiHA0AgCE2hDDjaAAADKETBgA4kg2dMCEMAHAkG0KYcTQAAIbQCQMAHMmGTpgQBgA4EiEMWKCkpMR0CQAsRQgDAByJThgAAEMIYQAADLEhhPmKEgAAhtAJAwAcyYZOmBAGADiSDSHMOBoAAEPohAEAjmRDJ0wIAwAcyYYQZhwNAIAhdMIAAEeyoRMmhAEAjmRDCDOOBgDAEDphAIAj2dAJE8IAAEcihAEAMMSGEI77mvAXX3yhO+64Q4MHD1b//v01YcIEtba2pqM2AAD6tLg64W+++UaTJ0/Wtddeq61btyo/P1//+Mc/dMEFF6SpPACAzTKhm01GXCH81FNPyev1av369dF9I0eOTHVNAAAwju5uy5YtKi0t1axZs5Sfn6+JEydq7dq1Z3xPKBRSMBiM2QAAQJwh/Nlnn6murk4/+tGP9MYbb2jevHm6//779cILL/T4Hp/PJ4/HE928Xm/SRQMA+r6TnXAym9NlReKoMicnR6Wlpdq1a1d03/3336+Wlha99957p31PKBRSKBSKvg4Gg/J6vZowYYKys7OTKB0A0NvC4bDa2toUCATkdrvTskYwGJTH49G1116r889P/Es8x48f1zvvvJPWWpMVVyc8dOhQjRkzJmbf6NGj1d7e3uN7XC6X3G53zAYAAOK8MWvy5Mnav39/zL4DBw5oxIgRKS0KAAAbbsyKK4QfeOABlZeX64knntAtt9yi999/X/X19aqvr09XfQAAS9kQwnGNoydNmqTNmzfrpZdeUnFxsX71q19p1apVmj17drrqAwCgz4r7iveNN96oG2+8MR21AAAQZUMnzG9HAwAciRAGAMAQG0I47gc4AACA1KATBgA4kg2dMCEMAHAkG0KYcTQAAIbQCQMAHMmGTpgQBgA4kg0hzDgaAABD6IQBAI5kQydMCAMAHMmGEGYcDQCAIXTCAABHsqETJoQBAI5ECAMAYIgNIcw1YQAADKETBgA4ViZ0s8kghAEAjsQ4GgAAy6xZs0ZFRUXKzc1VSUmJ3n333bStRQgDABzpZCeczBavTZs2qbq6WkuWLNHevXt11VVXqbKyUu3t7Wn4CwlhAIBDpSqEg8FgzBYKhXpcc+XKlbrnnnt07733avTo0Vq1apW8Xq/q6urS8jcSwgCAPs3r9crj8UQ3n8932uO6urrU2tqqioqKmP0VFRXatWtXWmrjxiwAgCOl6sYsv98vt9sd3e9yuU57/JEjRxQOh1VQUBCzv6CgQB0dHQnXcSaEMADAkVIVwm63OyaEzyYrK+uU83TflyqMowEAkDRkyBBlZ2ef0vUePnz4lO44VQhhAIAj9fbd0Tk5OSopKVFjY2PM/sbGRpWXl6fyT4tiHA0AcCQTP9ZRU1OjOXPmqLS0VGVlZaqvr1d7e7vmzZuXcB1nQggDABzJRAjfeuut+vrrr7V8+XIdOnRIxcXFev311zVixIiE6zgTQhgAgP8yf/58zZ8/v1fWIoQBAI7Eb0d3M3LkSGVlZZ2yVVVVpas+AIClTPxsZW+LqxNuaWlROByOvv7b3/6m66+/XrNmzUp5YQAA9HVxhfBFF10U8/rJJ5/UD3/4Q11zzTUpLQoAABvG0QlfE+7q6tKLL76ompqaM/6SSCgUivmx7GAwmOiSAACL2BDCCf9Yx6uvvqpvv/1Wd9555xmP8/l8MT+c7fV6E10SAIA+JeEQXrdunSorK1VYWHjG42praxUIBKKb3+9PdEkAgEW4MasHn3/+ud566y298sorZz3W5XL1+MQKAAB6wji6B+vXr1d+fr6mT5+e6noAALBG3J3wiRMntH79es2dO1fnn89vfQAA0sOGTjjuFH3rrbfU3t6uu+++Ox31AAAgiRA+rYqKioz4wwAAmc2GEOZ5wgAAGMJFXQCAY2VCN5sMQhgA4EiMowEAQNrQCQMAHMmGTpgQBgA4kg0hzDgaAABD6IQBAI5kQydMCAMAHMmGEGYcDQCAIXTCAABHsqETJoQBAI5ECAMAYIgNIcw1YQAADKETBgA4kg2dMCEMAHAkG0KYcTQAAIbQCQMAHMmGTpgQBgA4kg0hzDgaAABD6IQBAI5kQydMCAMAHMmGEGYcDQCAIXTCAABHsqETJoQBAI5ECAMAYIgNIcw1YQAADKETBgA4ViZ0s8kghAEAjpRsAGdCgDOOBgDAkLhC+Pjx43rkkUdUVFSkfv366ZJLLtHy5ct14sSJdNUHALDUyRuzktmcLq5x9FNPPaVnn31WGzZs0NixY7V7927ddddd8ng8WrRoUbpqBABYyIZxdFwh/N577+mmm27S9OnTJUkjR47USy+9pN27d6elOAAA+rK4xtFTpkzR22+/rQMHDkiSPvjgA+3cuVM33HBDj+8JhUIKBoMxGwAAZ8M4upvFixcrEAho1KhRys7OVjgc1ooVK3T77bf3+B6fz6fHHnss6UIBAHaxYRwdVye8adMmvfjii9q4caP27NmjDRs26De/+Y02bNjQ43tqa2sVCASim9/vT7poAAD6grg64QcffFAPPfSQbrvtNknSuHHj9Pnnn8vn82nu3LmnfY/L5ZLL5Uq+UgCAVWzohOMK4e+++07nnRfbPGdnZ/MVJQBAyhHC3cyYMUMrVqzQ8OHDNXbsWO3du1crV67U3Xffna76AACWIoS7eeaZZ/TLX/5S8+fP1+HDh1VYWKif//znevTRR9NVHwAAfVZWpJf/qRAMBuXxeDRhwgRlZ2f35tIAgCSFw2G1tbUpEAjI7XanZY2TOZGbm6usrKyEzxOJRPT999+ntdZk8QAHAIAj2TCO5gEOAAAYQicMAHAkGzphQhgA4Eg2hDDjaAAADKETBgA4kg2dMCEMAHAkG0KYcTQAAIbQCQMAHMmGTpgQBgA4kg0hzDgaAOBIkUgk6S2dVqxYofLycvXv318XXHBBQucghAEASEBXV5dmzZql++67L+Fz9Po4+uS/TMLhcG8vDQBI0sn/d/fWqDcV6wSDwZjXLpdLLpcr6fM+9thjkqTnn38+4XP0eggfPXpUkrRv377eXhoAkCJHjx6Vx+NJy7lzcnJ08cUXq6OjI+lzDRw4UF6vN2bf0qVLtWzZsqTPnQq9HsKFhYXy+/3Ky8tL6hFVJwWDQXm9Xvn9fsc+qioT8DmmBp9j6vBZpkaqP8dIJKKjR4+qsLAwBdWdXm5urg4ePKiurq6kzxWJRE7JmlR0wanS6yF83nnnadiwYSk/r9vt5j/UFOBzTA0+x9Ths0yNVH6O6eqA/1tubq5yc3PTvk53y5Yti46Ze9LS0qLS0tKUrMdXlAAA+D8LFizQbbfddsZjRo4cmbL1CGEAAP7PkCFDNGTIkF5bL+ND2OVyaenSpY6a8WciPsfU4HNMHT7L1OBzTJ/29nb9+9//Vnt7u8LhsNra2iRJl156qQYOHHhO58iKZMJPigAA4DB33nmnNmzYcMr+d955R1OnTj2ncxDCAAAYwi9mAQBgCCEMAIAhhDAAAIYQwgAAGJLxIbxmzRoVFRUpNzdXJSUlevfdd02XlFF8Pp8mTZqkvLw85efna+bMmdq/f7/psjKez+dTVlaWqqurTZeScb744gvdcccdGjx4sPr3768JEyaotbXVdFkZ5fjx43rkkUdUVFSkfv366ZJLLtHy5ct14sQJ06Whm4wO4U2bNqm6ulpLlizR3r17ddVVV6myslLt7e2mS8sYO3bsUFVVlZqbm9XY2Kjjx4+roqJCnZ2dpkvLWC0tLaqvr9f48eNNl5JxvvnmG02ePFk/+MEPtHXrVn388cf67W9/m/CzWm311FNP6dlnn9Xq1av1ySef6Ne//rX+53/+R88884zp0tBNRn9F6corr9QVV1yhurq66L7Ro0dr5syZ8vl8BivLXP/617+Un5+vHTt26OqrrzZdTsY5duyYrrjiCq1Zs0aPP/64JkyYoFWrVpkuK2M89NBD+stf/sJEK0k33nijCgoKtG7duui+m2++Wf3799fvf/97g5Whu4zthLu6utTa2qqKioqY/RUVFdq1a5ehqjJfIBCQJA0aNMhwJZmpqqpK06dP17Rp00yXkpG2bNmi0tJSzZo1S/n5+Zo4caLWrl1ruqyMM2XKFL399ts6cOCAJOmDDz7Qzp07dcMNNxiuDN1l7M9WHjlyROFwWAUFBTH7CwoKUvIMShtFIhHV1NRoypQpKi4uNl1OxmloaNCePXvU0tJiupSM9dlnn6murk41NTV6+OGH9f777+v++++Xy+XSz372M9PlZYzFixcrEAho1KhRys7OVjgc1ooVK3T77bebLg3dZGwIn9T9OZGne3Ykzs2CBQv04YcfaufOnaZLyTh+v1+LFi3Sm2++aeTxa33FiRMnVFpaqieeeEKSNHHiRH300Ueqq6sjhOOwadMmvfjii9q4caPGjh2rtrY2VVdXq7CwUHPnzjVdHv5LxobwkCFDlJ2dfUrXe/jw4VO6Y5zdwoULtWXLFjU1NaXlec99XWtrqw4fPqySkpLovnA4rKamJq1evVqhUEjZ2dkGK8wMQ4cO1ZgxY2L2jR49Wi+//LKhijLTgw8+qIceeij6SL5x48bp888/l8/nI4QdJmOvCefk5KikpESNjY0x+xsbG1VeXm6oqswTiUS0YMECvfLKK/rzn/+soqIi0yVlpOuuu0779u1TW1tbdCstLdXs2bPV1tZGAJ+jyZMnn/IVuQMHDmjEiBGGKspM3333nc47L/Z/79nZ2XxFyYEythOWpJqaGs2ZM0elpaUqKytTfX292tvbNW/ePNOlZYyqqipt3LhRr732mvLy8qKTBY/Ho379+hmuLnPk5eWdch19wIABGjx4MNfX4/DAAw+ovLxcTzzxhG655Ra9//77qq+vV319venSMsqMGTO0YsUKDR8+XGPHjtXevXu1cuVK3X333aZLQ3eRDPe73/0uMmLEiEhOTk7kiiuuiOzYscN0SRlF0mm39evXmy4t411zzTWRRYsWmS4j4/zxj3+MFBcXR1wuV2TUqFGR+vp60yVlnGAwGFm0aFFk+PDhkdzc3Mgll1wSWbJkSSQUCpkuDd1k9PeEAQDIZBl7TRgAgExHCAMAYAghDACAIYQwAACGEMIAABhCCAMAYAghDACAIYQwAACGEMIAABhCCAMAYAghDACAIf8L8vln9nDKM7AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mexican_hat = filters.laplace(image2)\n",
    "\n",
    "plt.imshow(mexican_hat, cmap='gray')\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3c74867-f1cd-404e-b411-38512cd02109",
   "metadata": {},
   "source": [
    "## Laplacian of Gaussian\n",
    "\n",
    "We can also combine filters, e.g. using functions. If we apply a Gaussian filter to an image and a Laplacian afterwards, we have a filter doing the _Laplacian of Gaussian_ (LoG) per definition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1689081f-d994-4e13-be1a-c6fb5c8237fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def laplacian_of_gaussian(image, sigma):\n",
    "    \"\"\"\n",
    "    Applies a Gaussian kernel to an image and the Laplacian afterwards.\n",
    "    \"\"\"\n",
    "    \n",
    "    # blur the image using a Gaussian kernel\n",
    "    intermediate_result = filters.gaussian(image, sigma)\n",
    "    \n",
    "    # apply the mexican hat filter (Laplacian)\n",
    "    result = filters.laplace(intermediate_result)\n",
    "    \n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "728dc716-97fc-4dfe-872e-bbbef23f08d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x1d8687ac6a0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "log_image1 = laplacian_of_gaussian(image2, sigma=1)\n",
    "\n",
    "plt.imshow(log_image1, cmap='gray')\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d20498a9-8c23-4515-823b-e9986f8a5714",
   "metadata": {},
   "source": [
    "## Interactive filter parameter tuning\n",
    "To understand better what filters are doing, it shall be recommended to apply them interactively. The following code will not render on github.com. You need to execute the notebook locally use this interactive user-interface."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4aeb2bae-e68d-4372-95c1-316cd897969a",
   "metadata": {},
   "outputs": [],
   "source": [
    "image3 = imread('data/mitosis_mod.tif').astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "050fc927-bd57-4d49-8ad0-0b7af7d80bc7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "78f43dea98774bdeba1e7f1d7c2711a1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(interactive(children=(FloatSlider(value=0.0, description='sigma', max=25.0, step=1.0), Output()…"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stackview.interact(laplacian_of_gaussian, image3, zoom_factor=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67499cf3-d0b1-40f4-b5d3-6a103e43015a",
   "metadata": {},
   "source": [
    "## More filter examples\n",
    "We demonstrate some more typical filters using this nuclei example image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3ae20d23-9e96-4380-b8a0-69cff9f16b6d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d86893b6d0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(image3, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f1b5f95-e5be-4bd7-a62f-4ade460756d5",
   "metadata": {},
   "source": [
    "## Denoising\n",
    "Common filters for denoising images are the mean filter, the median filter and the Gaussian filter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9d184687-067a-4d8a-b853-73aa869b4789",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d8689a10a0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2z6xNtsc1NTW0zcmTJ7vqWs7xw4cPx8rY2p84cSJWZoXiYevsDZsD8PmztfOGhgL4+FmeHBaex+rfe56OHz9O22R7z+ZkOexZnqFDhw7FyphYwjqjXhFCiMiJzZMJckJERl70JCSEECI1ZISEEEKkhoyQEEKI1JAREkIIkRpFK0zo7u7OcyoypyUAHDt2LFbmjS4Q4kT3OvOsusyR681bBPid8yHOzKTRDbxiB+vNbW8+IlbPcph7r7fWiTm9WU6YbDYbK7vqqqtom0yYMHXq1FiZJSJgY2J5glgUhZDzECLe8UZ8YOepr6+PtsnEGkeOHHGPadKkSbEydo9a55HBBAPe/E4AF1Sx+TMRgCUyYv2HiJxYZAomsgrJw1V4P4assZ6EhBBCpIaMkBBCiNSQERJCCJEaMkJCCCFSQ0ZICCFEahStOq63tzdPBWKp45iqw1LPFGIpwbwhdqx+vCFRvHmPrP69YVKsMXlJGqrD6tur2EsadoeVWaFf6urqYmVeJdzs2bNpm7NmzYqVsTWxQsdMnDgxVtbd3R0rY/eIpcD0qpeset7QWAwrb1B/f3+srKKiIlbGlIEAV6h5Q2hZsLrsO8cK4cXC9nhDjVn3TYgSjsH2NKmKsLB/5RMSQghREsgICSGESA0ZISGEEKkhIySEECI1ilaYMDAwkOdQZuEzAO4884ZuCXG8MWegdb3X4R4SdscbYsgKZ+N1FLI5Wdd655kUNnfL4c7qsjw9n/jEJ+j1TETABAeXX355rCwkbA+DOeEBoKurK1bGwv7s27fP1Q/AHfbeEDVWuTe/lJV7h51dNiZLWDAwMBAr84parPuGzckbsgjwi4e8ghyrrvc7z6rr/S6y5ilhghBCiJJERkgIIURqyAgJIYRIDRkhIYQQqVG0woShoSGXM545wNjbv958GYDfcRfizPQ6KK0xeXMPhQgbvDllkrZpOTO9Yg9vBAoAyGQyrrLLLruMXr9w4cJYGRMmXHrppbGyCRMm0DbZ+FmeGSsSAFs/lpMm5DwxcUBIdAG2T16xQkgEDdZPiCjFmwfMEkuwNQmJ0sLWhJ1Hr6jDIkREECI+KiQkyowXPQkJIYRIDRkhIYQQqSEjJIQQIjVkhIQQQqRG0QoTRkZG8pxtIU425jgMcboy5xtzplrOPOZ49IZPD3G6egUUQLI3ty28da16XgEHW2fLuc3mVF1dHSurr6+n17OoByyKAjtPllDl2LFjsbI33ngjVtbR0UGvZ+UslQNLEWA53L3rbJ1xNle29iwKhBVphLXpFUBY/bN7jM2J3bMAP2dsTlZEl6SRThhsT72pXqzyJFEUgPg6hUSj0ZOQEEKI1JAREkIIkRoyQkIIIVJDRkgIIURqBBmh1tZWXH/99aiursbUqVPxpS99KeY0jaIIzc3NqK+vR0VFBRYvXoy9e/ee00ELIYQ4PwhSx7W3t+POO+/E9ddfjw8++ABr167F0qVL8eqrr6KqqgoAsH79emzYsAFbtmzBlVdeiXXr1mHJkiXo6OigKiWLU6dO5SkxLLVFSFiQQpLm3glRaHnVdUx1BXBFDFP+hKjjkobqYH2FqAhZXa/Kx9o7r2qrsrKSXu9VNg4ODsbKjh49Stt86623YmWvvPJKrOzll1+m17N8QgcPHoyVsVA+Ft7QLSFnnK2994xYbYbkAWOqNXZ2WL1x48bRNtk9xlSIISG8LMWit543n5Gl+PMq4bx7zOqG5BMKMkLPPPNM3v8/+uijmDp1Knbt2oUvfOELiKIIGzduxNq1a7F8+XIAwNatW5HNZrFt2zbccccdId0JIYQ4z0nkEzodhHHSpEkAgAMHDqCrqwtLly7N1clkMli0aBF27txJ2xgeHkZfX1/enxBCiAuDszZCURThnnvuwY033piLMnz6Z4NsNptXN5vN0p8UgA/9TLW1tbm/6dOnn+2QhBBClBhnbYTuuusuvPLKK/j3f//32GeFvy9GUWT6KtasWYPe3t7cX2dn59kOSQghRIlxVmF7vve97+Gpp57C888/n5dXpa6uDsCHT0TTpk3LlXd3d8eejk6TyWRMB9qZWM5x5sj35sSxDKPXIZfU4R6SA8QbdsfrOLT6Dwq3QcYUkgPFG/YnJJ+QN1fMu+++S6//wx/+ECtjeX7Yz8aWMGHfvn2uMiY2AIAjR47EyliYGG8+HsC/d9b1IXmnvG2ye5nVtc44Oyenv5POpLa2NlZmCVVOC67O5MSJE7GygYEBer33nLA2rfVkax9yL3pFAyFih0JGLWxPFEW466678MQTT+CXv/wlGhoa8j5vaGhAXV0d2tracmUnT55Ee3s7TRYmhBDiwiboSejOO+/Etm3b8J//+Z+orq7O+Xlqa2tRUVGBsrIyNDU1oaWlBY2NjWhsbERLSwsqKyuxYsWKUZmAEEKI0iXICG3atAkAsHjx4rzyRx99FN/61rcAAKtXr8bQ0BBWrVqFnp4ezJ8/Hzt27Ah6R0gIIcSFQZAR8vyWWFZWhubmZjQ3N5/tmIQQQlwgFG0+ocKICSHRDZLmSvEKBkIiCSQVOzBHX8jb5KwvbxQGSyzhfcM+qYPVm3cI4G+zM6fx66+/Tq8vfCEb4M5pJgxgeYMALmxgYoPjx4/T64eHh2NlbE3YerL9BPxvzVvRDbxRSVg9a0wsagE7o9benymGOg0TIdTU1MTKTr/r6BnT1KlTY2XW3jFhgvf7IeT7KSRCAYPdNyyyhPVdULinyickhBCiJJAREkIIkRoyQkIIIVJDRkgIIURqyAgJIYRIjaJVx5WVleWpQLyqDKtuSJ6bpDDlEhsnq2cpybxhfyxVClsT75gsNRJbv5A5eVWM3vA+AN9nFhJl//799HoWUoUpC9k8rbV///33Y2VMjcTqhfTF9tMak6VQK8TKs8OYMGFCrIzth5Uzy6vgtELssP6ZspFdb42JhalhYxo/fjy9nq0/U+wxBacVmoq1yepa17NzxvaJzdN637OwL6njhBBClAQyQkIIIVJDRkgIIURqyAgJIYRIjaIVJhQ6qEPy5DAnm9cZx/oOxZv/xhuixmrTG3rFKmfXh+Ql+b8KP8LGZDk+vWM6nZq+EG+enhC8AowQmLCAtclCrwDcEc/atBzRzLnORAwsRE7I3rH71hoTEwd4cxxZeXLYWNk6W6ISts5MLMHmxAQ1gF9EYJ0x79lh37nW3hWun4QJQgghSgIZISGEEKkhIySEECI1ZISEEEKkRtEKE7wRE5jzzCtWsJxn3jf0Q97kt4QVZ1sPCMsr4nWOe8UKIWMKclKSvpjT1xoTE3Ywp7M1Jpa7h+0JG5O1d975hziSvRETrDGx/Dks4gArs9plYgW2T1bEAxZFwhtxAOD3OGvT6p/BhCpsTJYAhIkLmDCBiTqsaBVeYUSI8MorwLAoFEZImCCEEKIkkBESQgiRGjJCQgghUkNGSAghRGoUrTCh0CkW4oj+v4ouYDnfLIdgISHRCRghIgKviCEk5YV3/CFjYrAxWUIVy0Hs7ZuN1ZsGI0Q84+0b4Gectcn2yXJuT5w4MVbGohuwegCPBMBEAKxNaz1YXTYna+/YOWHjDxG6eNeZCVqsMYVEFWGwvth+sCgKgD8CCSsLSanjRU9CQgghUkNGSAghRGrICAkhhEgNGSEhhBCpISMkhBAiNYpWHVdeXu4K2+NVczFFjaWySXo9w1vXqucNgzFa1zPYnoTkzmF9MZWNNxcTwOcZkhfFqxgMgfUVokL0jp8pA5nizKrLyiwlG9s7Fo6GKeaYksvqn4W9sRSQbE1Z2B12dtg4AWBwcDBWFqJCHBgYiJWx88z2k/UN8D1hSjhLscbUgV71cEgILy96EhJCCJEaMkJCCCFSQ0ZICCFEasgICSGESI2iFSaMjIzkOcYsJ5vXaR0SFsNLUkdyyJjSFkZ464aER/K2ycoshzlzerN1DnHaekk6T0sAwZzObP7s3Fttspw6IaFXWI4mNk42ppBwMqyMOfutMTHxzPHjx2NlllCFnQe2TtacGKwvJsCwzjgTLISE7UkSrssSJhT2r3xCQgghSgIZISGEEKkhIySEECI1ZISEEEKkRtEKEy666KI85y0TIADJRACW88zrcLecvsyZ6c1LEpJ7J8SRzPpijks2J2vtk0YnYM5UNn82T2vtvTmWQvaewfoPyU8VkkuKOdy9ghzLuc3Gz8QK1jqxCANs/CG5c9h59J5Rq382fjZPK2ICw5uvzGq3r68vVsbWyRIWsD31RmGwytmesH5CxDde9CQkhBAiNWSEhBBCpIaMkBBCiNQIMkKbNm3Ctddei5qaGtTU1GDBggV4+umnc59HUYTm5mbU19ejoqICixcvxt69e8/5oIUQQpwfBBmhSy+9FA8++CBeeuklvPTSS/jjP/5j/Nmf/VnO0Kxfvx4bNmzAP/zDP+DFF19EXV0dlixZgv7+/lEZvBBCiNKmLEoYz2bSpEn4+7//e3znO99BfX09mpqacO+99wIAhoeHkc1m8dBDD+GOO+5wtdfX14fa2tpYPiFLNcZUJUzBEaJEY20yRYyV44ipuZjShJVZuVasvDCFDA8Pu8uZSiYkbA1bE6bosXKtMEUPWxM2Jkulw/ry7qeFV91m3UpJQxmxsbIylmenrq6OtvnJT34yVuY9YwCfE1PxsXUKUboydZml+mL9e5WFIfml2PWWuq6rqytWdvjwYVeZ1ab37Fj3sjcPWMi5Lbx+ZGQEBw8eRG9v78eeq7P2CZ06dQrbt2/HwMAAFixYgAMHDqCrqwtLly7N1clkMli0aBF27tx5tt0IIYQ4jwl+T2jPnj1YsGAB3nvvPYwfPx5PPvkkrr766pyhyWazefWz2SzefPNNs73h4eG8f6UzDb0QQojzk+AnoU996lPYvXs3XnjhBXz3u9/F7bffjldffTX3eeHjWhRFH/n42Nraitra2tzf9OnTQ4ckhBCiRAk2QmPHjsUVV1yBefPmobW1Fddddx1++MMf5n57LvwNtLu7O/Z0dCZr1qxBb29v7q+zszN0SEIIIUqUxGF7oijC8PAwGhoaUFdXh7a2NsyZMwfAh07q9vZ2PPTQQ+b1mUyGOg8LhQmW45A51CzBgBcmDvCGqLFgdVn4kPr6eno9K2fXv/vuu/T6Q4cOxcpYXhVv6BOArzNzjlvhR7zrzJzDloDD60wNERGEiFIY3v5DwtF4wyNZzu3e3l5Xm+zeBPzCDta/tfbMkR4iImDXHzt2zHW9JVLyimdYPwC/x44cORIrY8KhEAEHw9oj79kLCeFV2GaI3i3ICN1///1YtmwZpk+fjv7+fmzfvh3PPfccnnnmGZSVlaGpqQktLS1obGxEY2MjWlpaUFlZiRUrVoR0I4QQ4gIhyAgdOnQI3/zmN3Hw4EHU1tbi2muvxTPPPIMlS5YAAFavXo2hoSGsWrUKPT09mD9/Pnbs2IHq6upRGbwQQojSJsgI/fjHP/7Iz8vKytDc3Izm5uYkYxJCCHGBoNhxQgghUqNo8wmNGTPG9Waw1wE2Go5gq2/m5GQO3gkTJsTKrrjiCtrmzTff7GrzTLn8mbAXhtn4WYglS1jAIkMwh73l3GbrzPaErb3lSPYKEyxhgTdXTEgEDm8/IXiFESdOnKDlR48ejZWx/Rw/fjy9nu0pWyc2TmvsXrHF4OAgvZ6JLZhYwRI2eGH9W5FK2PozsQZbE0uA4M2NFpKPyCvWsMZUeH1IRBA9CQkhhEgNGSEhhBCpISMkhBAiNWSEhBBCpEbRChNGRkZcqRy8jmjmCE7qSLacb0kc7g0NDbTN2bNnx8o+8YlPxMqqqqro9e+8806sbGBgIFbGnJnWPC1nbCHWW9YMrwDEEoWwsTLndEjEBa8jN2RMIZEpvPNnzm3LOT00NBQrY8GDLQEFa5dF8GBOeFbPapONs7u7m17PBAPegMjWeWBjYmXWGfemUAmJMMAEJGydrL3znnHvGWN9SZgghBCiJJAREkIIkRoyQkIIIVJDRkgIIURqyAgJIYRIjaJVx5WVlbkUFkzVwa5jihILryrEGh8LaeLNiWOpTyZNmuQqmzlzJr1+xowZsTIW4ocparwqOICP31L+sL1jyiN2vRU+hKmU2N4zxRzgD9vDlJXWefCuiXU9mxPrn62ddZ5Ynhs2dytEzrhx41zXs3o9PT20TTZ/lqfH2jsWisirOrPyLnmVnVY9by6p0TgP1t6z+8EbhsoaU+GehIRG0pOQEEKI1JAREkIIkRoyQkIIIVJDRkgIIURqFK0woRArxE5FRUWsjKUT9+YIAnioD6/DHOBOOSZCYG0yRy7AnZGszWnTptHrJ0+eHCubMmVKrKyrq8s9JuYgZusc4rS19qQQy/HJ1sQrLAiBXR+SnyppjiOvUMZaJ7YnLPeNJehhggF2LzKHf4iohGGJJdiesP69ebA+qrwQa07sHveGgQrJBxQSVswrQggJJVTYl8L2CCGEKAlkhIQQQqSGjJAQQojUkBESQgiRGkUrTBgzZkyec4s5PQGgvr4+VsZy6tTU1MTKWA4OABg/fnys7MiRI7EyK5KA10HMHP5eRygQFkmACRZY/2ydmMMa4A5e681zBlsn5iD15j8B/G+eW8IEr9M25G1yVpc54YOcuc51SpoLynJOe6NQsPOcNLqAtfdeEYJX5AP470crioPVbiFs7CHnga2TJZRhc2Lj9+YYAuJnTxEThBBClAQyQkIIIVJDRkgIIURqyAgJIYRIDRkhIYQQqVG06rjJkyfnKYBYiBkAyGazsbKpU6fGykLUGkwJxzh06BAt9/bFwnJY6jIWSoipfKwQO0wxOGHChFgZG7uliPEqrJKGD2FYqiVv+BFLzeQN6cKUQyGhW0Lw5p8JWU9W1xs2B0imbLT6YevH6obsnXdO1h5ZCrNCQpRs3rNjjd27zyFKW+/11noUrr3UcUIIIUoCGSEhhBCpISMkhBAiNWSEhBBCpEbRChNmzpyZ56yrrKyk9S6//PJYWUiYFga7ngkG+vv76fVMRMDCdzDHo+XsZ+Xs+hBnJLuerZPlCGZOyhAnvJWrxoO1n2zv2DhDwv54cxxZ68T2xOvEB/w5mkLWk82JnVHL4e49Z2w9Q8Y5GnmXQu4R795ZeMUSrMw6D955hoTtYYR8jxaOVfmEhBBClAQyQkIIIVJDRkgIIURqyAgJIYRIjaIVJtTU1OQ59ayICcxRxkQMIY47JgKwIhEwMplMrIw5rVmbIQ49huUcZ2IJlieIzd1aJ5aPiTlirYgLbK7eN8eTRkyw8F4fEnHA+za6JYDwihBYP+wsAlxAEvLWPjsT3gga1jy9ax8SmYKJLZjIKEQUwupaDns2Jm+b1neBNxpBiKDIex6te6mwTQkThBBClAQyQkIIIVJDRkgIIURqJDJCra2tKCsrQ1NTU64siiI0Nzejvr4eFRUVWLx4Mfbu3Zt0nEIIIc5DzlqY8OKLL+KRRx7Btddem1e+fv16bNiwAVu2bMGVV16JdevWYcmSJejo6EB1dbW7/aqqqjynouUQY84z5gxkzjirTebMZP1YYgXm+GR1mePQcgT39PTEygYHB2Nlx44do9d3d3e7rmf9W+kl2JqyOVlOW290BjampOkhrL33RjLwihWscrZ2IcIGNn9vGgqAn8cQ57jXke2NDmBdz+ZkReVg9y2rW1FREStLmvbAGhPbe+86hwh6QiJTsHvMK0LwnvFRT+Vw4sQJ3Hbbbdi8eTMmTpyYN5CNGzdi7dq1WL58OWbPno2tW7dicHAQ27ZtO5uuhBBCnMeclRG68847ccstt+Dmm2/OKz9w4AC6urqwdOnSXFkmk8GiRYuwc+fOZCMVQghx3hH8c9z27dvx29/+Fi+++GLss66uLgDxbKfZbBZvvvkmbW94eDjv/QL2PosQQojzk6Anoc7OTtx99934yU9+8pEvbxb+ZhlFkfnbcmtrK2pra3N/06dPDxmSEEKIEibICO3atQvd3d2YO3cuysvLUV5ejvb2dvzoRz9CeXl57gno9BPRabq7u2NPR6dZs2YNent7c3+dnZ1nORUhhBClRtDPcTfddBP27NmTV/btb38bs2bNwr333ovLL78cdXV1aGtrw5w5cwB8qBppb2/HQw89RNvMZDKuMDdWqA6m8PKGzWFqmtNjLsQbesUqZwoz9nS4b98+2ua0adNiZSyfkRVip6OjI1bGFHMhqhavoshSxzGVVBI1EeBX+VjnyascCskzk0RxZ5Wz69nYLYWUV/lk7TFrN4nqKqSuNSdvyKmQvUuqZPPC2gwJfWPd9wymDvTmAbOUjYVjDfkeCTJC1dXVmD17dl5ZVVUVJk+enCtvampCS0sLGhsb0djYiJaWFlRWVmLFihUhXQkhhLgAOOcBTFevXo2hoSGsWrUKPT09mD9/Pnbs2BH0jpAQQogLg8RG6Lnnnsv7/7KyMjQ3N6O5uTlp00IIIc5zFDtOCCFEahRtPqGDBw/mOSrPjMxwJizPEHMyMkm55YzzhhqxnG9ehzvL5/P222/TNnfs2BEru+KKK1xtWu2yED8sR5CVl4TN3xs6BeAOUrZO3rxD1piYIzskT463TcuJ73Vkhwhd2DhZPyEhclg/IeGR2H56BTmAP0+P5YRn7bK6bO7WGfeuaUiIHa+oI2Ttvf0AfPzsvmVCD+u+Cwl7VIiehIQQQqSGjJAQQojUkBESQgiRGjJCQgghUqNohQnd3d15Tkkrpw1zZk6dOjVWxhxnzAkPAMePH4+VHT58OFYWImxgjkM2disfEIsMURgeCbAdh729vbEy5nhk62Q5XZnYg83dcpB68+QwrHpeR3JSYQPrx3rr3uu0DZmT1ZcXdj9Za+Idk/et+xChC4t+YuHdJ4ZVzxprIdZ+eNc0JCKLVzzj3Q+rL2++MCC+9qOeT0gIIYQ4F8gICSGESA0ZISGEEKkhIySEECI1ZISEEEKkRtGq43p6evIUI5bSg6k1mJKMKblYPh6Aq+NYOJyBgQF6vTesR0i+EHY9UzhZIU3YmLyqLSuLLrueqZksdZ1XQeNVAwH+vCzWOjGVElM4hajDvPscko+IjZ+pw6wxeVVn1t5Z4YA811vrwULHhFzP1oS1GaKWZLDrrfPE1tm7dtaYvGF3rL1Poqz0fr9IHSeEEKIkkBESQgiRGjJCQgghUkNGSAghRGoUrTBhaGgozwHJQsxY5SxEDXOuWyEomGCB9WM5ba1yD1aIG9ZmSJ4c5rhkhIQP8eakCclp4xUheOdj9WM5Ttn8vaFbQkK/sHlaDmNvnp2QfECj4Rz3CjgsoQubp3fuFmycIaGAWF22n9aYvCKGkHBZXhGF9V3C+mJtes8IqythghBCiJJARkgIIURqyAgJIYRIDRkhIYQQqVG0woT3338/z6lpObqYCIE51FjuIEvs4I0uEPLWPXMSsjLLwel1ZlpOV1bX+za5NU+vMzXpW/dsTazzwOYUsnfsTHjXPkTswLDWiZ0T5kgOEcR48yZZ94i1foWEiEJYXfbWv+VwZ2NibbL9GD9+PG3TG4WCfQ9ZsEgnbO9C8gF59wPg68/EFt7cXIDyCQkhhChRZISEEEKkhoyQEEKI1JAREkIIkRpFK0woLy/Pc4xZb+0zxyFz/DFnpPU2OXOqMcef5QysrKyMlU2ePNlVL+nb4CzlBMAdj8zpnPTN6ZC0C9437EPwvg0eEgWCOY1DIkuw60OiG7Drk4olvKH/rfPoHRPDEhaw88gEA1bEherq6lgZO7vsenYvAnyd2JpWVFTQ61n0FdYmSz9jnQe2T97zACRL5WAJnwrXJOQ+1pOQEEKI1JAREkIIkRoyQkIIIVJDRkgIIURqyAgJIYRIjaJVx40ZMyZPYRGSF4UpRULCybC+WF1LKXLJJZfEymbMmBErq62tjZXV1NTQNpnqjY3JCh/y5ptvxsqYeoYpb0JCcFiKHC9eJVpImJKQXC3ecDYheWpC1o/B+veqjywlGht/SI4mRtI8NV4lXF1dHb2e1WVlbO+tuXtz91iKPTano0ePxsrYGbGUrmzvQ+4773ch68cbmkrqOCGEECWBjJAQQojUkBESQgiRGjJCQgghUqNohQmFjjLLIRbiPDvbvgF/PiAAmDhxYqxs+vTpsbJJkybFyqyQGtOmTYuVMRHBoUOH6PXMwfrGG2/Eyrz5mQAeZiVEwOElJOwOw+t0tWB9sTAtLDSS1T/bZ2vvk+QjstbJG44mJJcUg60JC68DcCc+E/lMmDCBXs/OCZtniACDrQnrxxIwsL1j+8TWyconxO7HEOFVSN4pL4VthvShJyEhhBCpISMkhBAiNWSEhBBCpEaQEWpubkZZWVne35kvjkVRhObmZtTX16OiogKLFy/G3r17z/mghRBCnB8ECxM+/elP4xe/+EXu/890XK5fvx4bNmzAli1bcOWVV2LdunVYsmQJOjo6TGekxWkjd5qQ6AbeiAlJsXKIMAdrVVVVrIzlMGHXAsDAwECsjDlNmQAC4E5OJnZgTk+WnwnwCzgsxzrbJ1aXzTMkgkaIsME7JtaPNSavc9qCrak3H5HlME8q3vHuE7tHrNw9LOcWiypinScraoGnntUmW2dvZAjAFlF42rT2yHuPWnNi7bK6bE6W+KawzVEVJpSXl6Ouri73d1q9EkURNm7ciLVr12L58uWYPXs2tm7disHBQWzbti20GyGEEBcAwUbotddeQ319PRoaGvC1r30N+/fvBwAcOHAAXV1dWLp0aa5uJpPBokWLsHPnTrO94eFh9PX15f0JIYS4MAgyQvPnz8djjz2GZ599Fps3b0ZXVxcWLlyIo0ePoqurCwCQzWbzrslms7nPGK2traitrc39WT8nCSGEOP8IMkLLli3Dl7/8ZVxzzTW4+eab8bOf/QwAsHXr1lydwt+loyj6yBcD16xZg97e3txfZ2dnyJCEEEKUMIkk2lVVVbjmmmvw2muv5VRyhU893d3dsaejM8lkMqipqcn7E0IIcWGQKGzP8PAwfv/73+OP/uiP0NDQgLq6OrS1tWHOnDkAPlRktbe346GHHgpu+/3333eFVvGGZAnJP+MNPWOFs2FKFaZuYyodq01v+BBLUcOUcCxEj1clA/DwJ151GuAPncPGZKnbvLmgrDGxut4cQ9YZY+GNQpRs7HovIapShrXO3tA17IwzFRzAw1gxmNIUAPr7+2NlVu6hQkKUZGxOlmqM7R37LmEqQmtM7OyFnBHv2WNzGg2VcZAR+pu/+RvceuutmDFjBrq7u7Fu3Tr09fXh9ttvR1lZGZqamtDS0oLGxkY0NjaipaUFlZWVWLFixTkfuBBCiNInyAi9/fbb+PrXv44jR47gkksuwec//3m88MILmDlzJgBg9erVGBoawqpVq9DT04P58+djx44dwe8ICSGEuDAIMkLbt2//yM/LysrQ3NyM5ubmJGMSQghxgaDYcUIIIVKjaPMJjRkzJs+BFpI/xhsmJSR/C3NQWmPq6emJlX3Uu1JnYoUeYaFOmCPcUhd6Q42wMsuJzcqZ0zQk/Ig35JLlCLac+94xefv3hs0JGZMlSmFjYmGYWP/WmKxcWIVY55GtP7tv2PUsFA/Azy5bOybyAXjuISYSYgII6zyw+87aJwZrl+0dO08hoYRC8qqxdtk6MQHF4OAgbbOwbki+Lj0JCSGESA0ZISGEEKkhIySEECI1ZISEEEKkRtEKEwrzCYXkpPHWs9r0OtWYgxHgkQiYWIE5/qZMmeLuizltrSjk7G1y5uBlDsoQBydzmlp7xNbZ6/S1HOvMYR6y96x/1hdbe+ttcu+asPMA8LfhvZFCQvIusTFZuaTYWL05iixRSRKHOQAMDQ3Fylg+H3buk659iNCF7QkTcFjfLwx2Hq0znkSE4BXZhKAnISGEEKkhIySEECI1ZISEEEKkhoyQEEKI1ChaYcLIyEieA89ysDInpzfFgOUw9zoTQ8Knv/3227Ey5ni0HMEs/P2RI0fc/TNhxOHDh2NlzGlriQW8YgnLQcr2zutct0QA3kgA1pyYg9YbgSPkLfGQiAsMVtdaZwbbJ3b2rIgJ3tQkzLl94sQJ2iY7oyzFQYhQhvXFoiBYkQDYd0lSAQg7o6x/64x70ylY68TWlIk62BmxosQU3jdekQqgJyEhhBApIiMkhBAiNWSEhBBCpIaMkBBCiNSQERJCCJEaRauOK8wnZKmZmCKG1fXmCLLKvYo5gKuMmKKF1Tt+/Dhtc/z48a7+LeUM64spctjcQ/LksP6t8CPesD9MTWQpG9neh+SSYmNlijnWT9LzFJKnxhvyyFK3sb1jda0xsbpM7cjOnaXqZGNia2eF2GFKNq9izwpHw84DG1NIGCh2j7N6IerbELUma5fdY2zvvPed1HFCCCFKAhkhIYQQqSEjJIQQIjVkhIQQQqRG0QoTTp065QrbwxzZzMkYEhKFOfmY09VyZnqdzqzMcuKzkCbMGRqSI4n1z+pZzkjmfAxx2rK63r0Lyd/CzkhI2B+vk9UKacLGz86TFXLIGzYoqSiEYYkAvONn/VsOd3bG2Zyqq6vdY2JnnJ0xS4DhDS1lnScmgmDzZ2INK+8SO2eszDq3TMDBxuTN1cbqhnzf6klICCFEasgICSGESA0ZISGEEKkhIySEECI1ilaYUIjl+PM6bUejf8vx53XKsestZ6Q3T06IQ9Ab8cBqczRy/7A18UZRsPpKKuDwOvyteTIHrzdaBOAXe4S8pW4JFryw9feKFaycWWxOITm3WHQEVsb2w1o7Nv7+/v5YmXWeWN6lkBxLDK+oxLpHvJEYQu67wrqKmCCEEKIkkBESQgiRGjJCQgghUkNGSAghRGrICAkhhEiNolXHjYyM5CmVvIoQwB/mxQpLwVQhIYoab+iYpGMKCUfjDdvDQnpYbXrHVFlZSa9neNc5RInGxmQp/tj1TE0UkqOIlbN+QvaOzYntnXVG2fUh9xg7O2xOTMlmhQJiCjFvvjCAqz29OYqsubPxs3W2FHsMbx6vkO+XkBA7bPxs7ZkSzhuaSuo4IYQQJYGMkBBCiNSQERJCCJEaMkJCCCFSo2iFCWPGjMlzdlmOLubk9DpdLSeb1xlqOQNZqJEQYQPDGzYoqdOWjd3Km2T15WkT4I5PNs8QYYEV9ijJ9d5QSNZ6JJknwM+jV6wQIpYIEYAwvKGALCe+1xF+/Phxej1zuHtDNoWEMWJrYoWzYeeJzYn1z+YD8HPmFVNZY0oq6JEwQQghREkiIySEECI1ZISEEEKkRrAReuedd/CNb3wDkydPRmVlJT7zmc9g165duc+jKEJzczPq6+tRUVGBxYsXY+/eved00EIIIc4PgoQJPT09uOGGG/DFL34RTz/9NKZOnYo33ngDEyZMyNVZv349NmzYgC1btuDKK6/EunXrsGTJEnR0dKC6utrd1wcffJDn7LIcf6ORa4U5Hplz3nJEe53GjBDnNMNyZiaJmGA5+70Oe2vs3ogL7PqhoSHaJssfw9q09o4JXbyiFEvA4XXuh6xTSMQFLyF7781vFXIt6yskugEjSRQFq5ydB+s8eSOleMUrFqyuN29QSF/WPZ8kn1CQEXrooYcwffp0PProo7myyy67LPffURRh48aNWLt2LZYvXw4A2Lp1K7LZLLZt24Y77rgjpDshhBDnOUE/xz311FOYN28evvKVr2Dq1KmYM2cONm/enPv8wIED6OrqwtKlS3NlmUwGixYtws6dO2mbw8PD6Ovry/sTQghxYRBkhPbv349NmzahsbERzz77LFauXInvf//7eOyxxwAAXV1dAIBsNpt3XTabzX1WSGtrK2pra3N/06dPP5t5CCGEKEGCjNDIyAg++9nPoqWlBXPmzMEdd9yBv/zLv8SmTZvy6hX+bhhFkflb4po1a9Db25v76+zsDJyCEEKIUiXIJzRt2jRcffXVeWVXXXUVHn/8cQBAXV0dgA+fiKZNm5ar093dHXs6Ok0mk6HO4LKyMlfEBK+D1vvWeQiWI9rrTGX9Ww5C1ibrPyQdAHOGhkRMYNeHOCS9qSxYPSZAALgzljncrbfJ2fqxVBTeaBEAH3+IeMV7TticrHF6RQiWiICtszedQEgEjaTOdVbmjThg1WVYAg5v1AFWLyRSCes/ROjCCIkyU/gdPmoRE2644QZ0dHTkle3btw8zZ84EADQ0NKCurg5tbW25z0+ePIn29nYsXLgwpCshhBAXAEFPQn/1V3+FhQsXoqWlBX/+53+O3/zmN3jkkUfwyCOPAPjQwjc1NaGlpQWNjY1obGxES0sLKisrsWLFilGZgBBCiNIlyAhdf/31ePLJJ7FmzRr84Ac/QENDAzZu3IjbbrstV2f16tUYGhrCqlWr0NPTg/nz52PHjh1B7wgJIYS4MCiLkr7hdo7p6+tDbW1tzCdk/b7pfcmL/Q6b1CcU4r9J6hNidZP6hJJG0fb6hKy9S/KisTWmpD4hhvcFVovR8Al5U4aH+IRCokMn8QlZ/gKvT8jqx/tiKltPy6fj3WfrvvP6hLxjt8bE7tu0fUKdnZ3o7e1FTU3NR/fjGo0QQggxChRtPqHCf1lY/9Jg/ypI+tTB8P7rwerfGyrEejrz/qskJH+MNxxM0nAy1r98vU+s7EnE+pcrU815cwwBQEVFhev6kH8letWaIWF/koZM8irhLHWad/5snGyNrb7YfiYNlxXyFOu9x0J+VfHmbbLGmVQZmSS3mRUWzPt9zdCTkBBCiNSQERJCCJEaMkJCCCFSQ0ZICCFEahStMKFQom3hDdXBnImW88zryLbGxxx/Xie+1aZ3TkkFFMxBabXpdeKH9M/mycZkOUiZVJUJG6y9Z9czh713Pz+qr0LYOK0xefsJyb3jvZdCYP2HOMxD6rG+vK8cWOc2qaDI+2pIyH3L8IpCAL/QJUQsYYlqPOhJSAghRGrICAkhhEgNGSEhhBCpISMkhBAiNYpWmDBmzJg8Z1mIk40R4jD35rmxnL7et6eZk89yunqdmUnjRbG5W/HDvM75EOe2V5hgOUi9IgKLJJEpQqJ6eOP2fVS7HkIicHijj1jtMrFI0ogF3ggagD/OHPsusNZpNKKCeK+3vrOSxrz0CqJCvl8UMUEIIURJIiMkhBAiNWSEhBBCpIaMkBBCiNSQERJCCJEaRauOKwzbE6K2YOqbpFlMQ7J7esN6sP6TZte0VDpsrEmVP14lXMiYvCFVQrJOhszJq4wMCWniVYOFZHv1Zge11skb5sU6jyHhgDz9WFRVVcXKQkLssLVn6jpLmcj2JEQBytbJWxZy3yVVNnrvG+s8FK59yB7rSUgIIURqyAgJIYRIDRkhIYQQqSEjJIQQIjWKVphQ6OgLcXR5w1KEhALyhiSx+k8SNicEy7nNnLnMQRsSSsgrFrGuZ2vKxslC8YSchxBRi1eUEuKcTtKm1S67PiS/lPc8h4gl2PUheWa8YwoJTeXNJWWFAvLm3gkRgCTJNwb4xRaWgMO7pqye9f1UWDfke0xPQkIIIVJDRkgIIURqyAgJIYRIDRkhIYQQqVG0woTCfEIWXsGBN4rB6b4911vOSO+b6yFOV+8b6iFiCTbOEOe2N4qD5bBnb6mH9M/wzjMk2kVIFAhvm15RBsDX2TvPkFxQIVFFWDlbUzbOELGCt2/AH/EhpH9r/QqxRATeHEdsTNY82ZhChC5sTKz/kBxHyickhBCiJJEREkIIkRoyQkIIIVJDRkgIIURqFK0woTCVg+WYZ84zr3PZCrHvdQRbzjfvG9EhkQC8b26HOJKTvrntXecQAQjr37t2APDee++56oaMyetktc6o9TZ+ISFiidGImJA0sgTrq6KiIlY2btw42iZbJ+ZEZ3sM+COlsHoTJkygbbI1ZeMcGhqi17N9Yt87IRFZWPmJEyfcY/KmgghJgVK4ThImCCGEKAlkhIQQQqSGjJAQQojUkBESQgiRGjJCQgghUqNk1HGW2oKpV5jSIyRsjzdMC1O0AP5QIV6FkwULe2MprFi73pBHIaGAGJaixqv6YrC5A/aeePvxKsxClENsT0LWOYkSzht2BvCrywB+jzAlXGVlZazskksuoW2y65kSrq+vj17PytnajR8/PlZmKRgnTZoUK2PfL1OmTKHXDw4OxsrYGfWGGgOAnp4eWl6IFWKHqea8YaBC8nh50ZOQEEKI1JAREkIIkRoyQkIIIVKj6HxCp39rDnnj1mrj48pGq01v3aTjTDqmNNsM7ctbz+tTCvlt2+tPDBlTiA/AO6cQH1vSdWJz9Ua7sHwVzHfG6lqRTlhf3ogFVpve/i3/qNevEnIevOMP8TF6+7fGVHj96Xqe+7nojFB/fz8A2/GcFiE3kxBCiA+/z2traz+yTlmU9BHhHDMyMoJ3330X1dXV6O/vx/Tp09HZ2Ymampq0h3ZO6Ovr05xKgPNtTufbfADNqZiJogj9/f2or6//WMVv0T0JjRkzBpdeeimA/33Eq6mpKekNYWhOpcH5NqfzbT6A5lSsfNwT0GkkTBBCCJEaMkJCCCFSo6iNUCaTwQMPPODOx1IKaE6lwfk2p/NtPoDmdL5QdMIEIYQQFw5F/SQkhBDi/EZGSAghRGrICAkhhEgNGSEhhBCpUdRG6OGHH0ZDQwPGjRuHuXPn4te//nXaQ3Lz/PPP49Zbb0V9fT3Kysrw05/+NO/zKIrQ3NyM+vp6VFRUYPHixdi7d286g3XQ2tqK66+/HtXV1Zg6dSq+9KUvoaOjI69Oqc1p06ZNuPbaa3MvBi5YsABPP/107vNSm08hra2tKCsrQ1NTU66s1ObU3Nycyy12+q+uri73eanN5zTvvPMOvvGNb2Dy5MmorKzEZz7zGezatSv3eanO66yIipTt27dHF198cbR58+bo1Vdfje6+++6oqqoqevPNN9Memouf//zn0dq1a6PHH388AhA9+eSTeZ8/+OCDUXV1dfT4449He/bsib761a9G06ZNi/r6+tIZ8MfwJ3/yJ9Gjjz4a/e53v4t2794d3XLLLdGMGTOiEydO5OqU2pyeeuqp6Gc/+1nU0dERdXR0RPfff3908cUXR7/73e+iKCq9+ZzJb37zm+iyyy6Lrr322ujuu+/OlZfanB544IHo05/+dHTw4MHcX3d3d+7zUptPFEXRsWPHopkzZ0bf+ta3ov/5n/+JDhw4EP3iF7+IXn/99VydUpzX2VK0Ruhzn/tctHLlyryyWbNmRffdd19KIzp7Co3QyMhIVFdXFz344IO5svfeey+qra2N/umf/imFEYbT3d0dAYja29ujKDo/5hRFUTRx4sToX/7lX0p6Pv39/VFjY2PU1tYWLVq0KGeESnFODzzwQHTdddfRz0pxPlEURffee2904403mp+X6rzOlqL8Oe7kyZPYtWsXli5dmle+dOlS7Ny5M6VRnTsOHDiArq6uvPllMhksWrSoZObX29sL4H/TH5f6nE6dOoXt27djYGAACxYsKOn53Hnnnbjllltw880355WX6pxee+011NfXo6GhAV/72tewf/9+AKU7n6eeegrz5s3DV77yFUydOhVz5szB5s2bc5+X6rzOlqI0QkeOHMGpU6eQzWbzyrPZLLq6ulIa1bnj9BxKdX5RFOGee+7BjTfeiNmzZwMo3Tnt2bMH48ePRyaTwcqVK/Hkk0/i6quvLtn5bN++Hb/97W/R2toa+6wU5zR//nw89thjePbZZ7F582Z0dXVh4cKFOHr0aEnOBwD279+PTZs2obGxEc8++yxWrlyJ73//+3jssccAlOY+JaHoomifSWGipCiKgpKRFTulOr+77roLr7zyCv77v/879lmpzelTn/oUdu/ejePHj+Pxxx/H7bffjvb29tznpTSfzs5O3H333dixYwfGjRtn1iulOS1btiz339dccw0WLFiAT37yk9i6dSs+//nPAyit+QAfpquZN28eWlpaAABz5szB3r17sWnTJvzFX/xFrl6pzetsKconoSlTpuCiiy6KWf3u7u7Yvw5KkdPqnlKc3/e+9z089dRT+NWvfpVLuQGU7pzGjh2LK664AvPmzUNrayuuu+46/PCHPyzJ+ezatQvd3d2YO3cuysvLUV5ejvb2dvzoRz9CeXl5btylNKdCqqqqcM011+C1114ryT0CgGnTpuHqq6/OK7vqqqvw1ltvASjde+lsKUojNHbsWMydOxdtbW155W1tbVi4cGFKozp3NDQ0oK6uLm9+J0+eRHt7e9HOL4oi3HXXXXjiiSfwy1/+Eg0NDXmfl+KcGFEUYXh4uCTnc9NNN2HPnj3YvXt37m/evHm47bbbsHv3blx++eUlN6dChoeH8fvf/x7Tpk0ryT0CgBtuuCH2esO+ffswc+ZMAOfPveQmLUXEx3Faov3jH/84evXVV6Ompqaoqqoq+sMf/pD20Fz09/dHL7/8cvTyyy9HAKINGzZEL7/8ck5i/uCDD0a1tbXRE088Ee3Zsyf6+te/XtQSzO9+97tRbW1t9Nxzz+XJZQcHB3N1Sm1Oa9asiZ5//vnowIED0SuvvBLdf//90ZgxY6IdO3ZEUVR682GcqY6LotKb01//9V9Hzz33XLR///7ohRdeiP70T/80qq6uzn0PlNp8ouhD+Xx5eXn0d3/3d9Frr70W/du//VtUWVkZ/eQnP8nVKcV5nS1Fa4SiKIr+8R//MZo5c2Y0duzY6LOf/WxODlwK/OpXv4oAxP5uv/32KIo+lGE+8MADUV1dXZTJZKIvfOEL0Z49e9Id9EfA5gIgevTRR3N1Sm1O3/nOd3Ln65JLLoluuummnAGKotKbD6PQCJXanE6/H3PxxRdH9fX10fLly6O9e/fmPi+1+Zzmv/7rv6LZs2dHmUwmmjVrVvTII4/kfV6q8zoblMpBCCFEahSlT0gIIcSFgYyQEEKI1JAREkIIkRoyQkIIIVJDRkgIIURqyAgJIYRIDRkhIYQQqSEjJIQQIjVkhIQQQqSGjJAQQojUkBESQgiRGjJCQgghUuP/AZv9m/SQHuV3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "denoised_mean = filters.rank.mean(image3.astype(np.uint8), morphology.disk(1))\n",
    "\n",
    "plt.imshow(denoised_mean, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "40e5f991-d4bb-496e-9daf-165222df693d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d868a189d0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DYOMMcQQnDR3D+s/WkznxrZAmLHQLy1/D6lns27cvVsZEBJbYwSvAsMYUsia5WHmHvNd4T08PLR89enSsjI2T7VtLQMDGHxIeiZ2X5aJKen9j62GJCLzCKSaWsK6v3PZTyyckhBBChCAjJIQQIjVkhIQQQqSGjJAQQojUyFthwsmTJ7OcXbt27aL1mDPVm08oBOZ4tJy2rG7SnDbevElJBQisn0mdptY4WV+ZQ5ON3Zp71hZrxxqTV4TQ0NAQKxszZgw956RJk2JlIWINJkLwYjmSvZFGLAczK2eObMapU6dc9ay6TNRh9YmJPUKc5iF9ZbC8U4cPH46VBUUYcO4dK58Q28/sPuqNopAUPQkJIYRIDRkhIYQQqSEjJIQQIjVkhIQQQqSGjJAQQojUyFt13PHjx7PUGZZ6xJtHw6u6CqlrqWxYXW8IjKThaCxloFc1x+bOatur0gkJpRMyzwxvOBmrT+PHj4+VMYVVVVVVrOwv/uIv6DkrKytpeS5WGKht27bFypjC6vXXX4+VhYRuCQkjxUIEedfZ2jd9fX2xMrYfrXvBO++8EytjSroQ9ay3LlPBWbB7Qcj9yYulgGTrbKlNc7HuI0nyRulJSAghRGrICAkhhEgNGSEhhBCpISMkhBAiNfJWmPDWW28N2NnlDWdjOTi97YY4zL2EhO9gdS0HY4iDNxfLOeudJ8th7RWQhAgbmNOXheL51Kc+RY+fMWNGrIyF3WHChCuvvJKe0ytMYI51gIcDskKy5GKtEZsTJowICbk0GGGkTpw44WrH4tChQ656If0MaZ/tXbbvmQghRKTE+mTlNUsSisi6Z+SeMygM0YB7I4QQQiRERkgIIURqyAgJIYRIDRkhIYQQqZG3woSioqIsx1yIo8vrdLWckawt5iS0jmdOQuZ49DooAe5w954TSJYnKMnb0B/Xjrd9JlawnMNMmMH2wzXXXEOPr66ujpX96Z/+aayMiQ0sRzCDrSdzwoccHyKUYWvKxA7WW/deEQI7PmSe2B7x5i0KIST6CSMkUok3T0/Itcz6aYlK2PFsnVjfvUIVCROEEEIUBDJCQgghUkNGSAghRGrICAkhhEiNvBUm5GI5DpmTjYkQmDPUcnAyx2GICMD79nVI2gKvMzOpiCDkeG8UCuucbKxJ++9983zs2LH0+EWLFsXKxo0bl6hPjDfffDNWtnPnTlp3z549sTLmSGbpBEKc0yGpA9j1xNYzRITgFc+ECIq89UaMGEHrsvljYwoRlXjn2boWkqaCuPTSS2NlbD+F7Adrn3nQk5AQQojUkBESQgiRGjJCQgghUkNGSAghRGoEGaGWlhbMmDED5eXlGDduHL70pS+hvb09q04URWhqakJtbS1KS0sxd+5c7Nix47x2WgghxIVBkDqura0N99xzD2bMmIEPPvgAy5cvx/z587Fz504MHz4cALBy5UqsWrUK69evx8SJE7FixQrMmzcP7e3tKC8vd7fV39/vUkoxVQcLP+INUwL4w5+EhO1h4WRYO1Y+IO85LZWKN5QRm6eQfD4h6javQitk7dLk5MmTtHzXrl2xsp/97Gexsrfeeosev3v37ljZ8ePHY2UhCiWvkiwkzw6ry9bO2uPsWmZ1LVUru79495g1ztLS0lgZmztr7r25h1ifrGO9+YAsxZ837BEbkzVPufMcEkIqyAg999xzWf9//PHHMW7cOGzduhW33HILoijC6tWrsXz5cixcuBAAsGHDBlRVVWHjxo24++67Q5oTQghxgZPIJ9TT0wMAGDVqFACgo6MDXV1dmD9/fqZOSUkJ5syZgy1bttBz9Pf3o7e3N+sjhBDi4mDARiiKItx///24+eabMXnyZABAV1cXgHjq46qqqsx3ubS0tKCysjLzqaurG2iXhBBCFBgDNkL33nsvXnvtNfz7v/977Lvc3wejKDJ9BcuWLUNPT0/m09nZOdAuCSGEKDAGFLbne9/7Hp555hm8+OKLGD9+fKb8XC6Wrq4u1NTUZMq7u7tjT0fnKCkpoU7z4uJil5Pbm/MiJL8FIyTETppheywRAXNGMue+15FqwdbMWkev4ME7dsA/99Z+YCFyWBlbp23bttFz7t27N1bG/tj6n//5H3r8sWPHYmXe/FJJ5ylEfMNga285xtl+ZPPMws4AXMTAzjlp0iT3OVl5X19frOz999+nxzOxSnd3d6yMzYm1dl5RTohQhe0d1qcQoYq77ZDKURTh3nvvxVNPPYVf/epXqK+vz/q+vr4e1dXVaG1tzZSdPn0abW1tmD179vnpsRBCiAuGILN2zz33YOPGjfjP//xPlJeXZ/w8lZWVKC0tRVFRERobG9Hc3IyGhgY0NDSgubkZZWVlNDCkEEKIi5sgI7RmzRoAwNy5c7PKH3/8cXzrW98CACxduhQnT57EkiVLcOTIEcycORObN28OekdICCHExUGQEfL4VYqKitDU1ISmpqaB9kkIIcRFQt7mEzp9+nSWU9NyHLK3rBnMkWo5xr15TSy8b1QzJ5/l8PXmOLKEDcyZyd68DonCwObJm2PIgp0zRIDB6jIH68svv0yP9zrcWf4Y6032t99+O1Z27h27j+J9k92C9d3K5+PN5WTllEmUPyYgT02II/xc1JaPcvXVV7uOtX6pYRETzgmwPsrIkSPp8d79ePDgwU/o4f/hFXCEXHds75aVlbmPT4ICmAohhEgNGSEhhBCpISMkhBAiNWSEhBBCpIaMkBBCiNTIW3VcLpYKjqm5vHlJLCUZU5WwshDlEFNzsXw+ScNiWCFymCLHO3chSrSQHCQM1lbSOWFjZzl+AODo0aMDbidEjcRC8ViKM9Z/tneZEs5S+7E5ZfvB2uOWGiwXpmoNeWeQqRAtpkyZ4q6bC1PWAbz/rE/WmNh+YkGa2TpZ+4ldo2zvWGpN772MHW/lKMolJJ+QnoSEEEKkhoyQEEKI1JAREkIIkRoyQkIIIVIjb4UJQ4cOzXKyWw535tBL6nD3OtUsx6E3x1FI/hfWV9Z+SO4edjybOwvWf6/TFPDnM2LzaY2TlbP1tNZ43759sTLvPIWIZ0JCQ7G63rljYWcA7nBneyTk+IkTJ8bKQsbJHOFMlPHRHGafBJv7pPvJ68QH+DxVVla6+hRyLR4/fjxWFiIoYqIWNk5r7by5wRh6EhJCCJEaMkJCCCFSQ0ZICCFEasgICSGESI28FSbkEuIQ80YsCMndw9oPETZ430a3nPje/C8heJ3G1lvzbPwhfUri8Lfy5ISsE4PNPxMBsGgXSdux1p6JA1hd5gS38nCNGTMmVsbWbtKkSfR4BjuetR+ydmyco0aNcvfJm6PJ2uPsHsFECNY8s7qsrZqamlhZX18fPaf3urHm2RuBIyQCSBL0JCSEECI1ZISEEEKkhoyQEEKI1JAREkIIkRoFI0ywHN5e5xlzvFnOSG/71lv3XsEBqxfSpxCxAnOae48PcVCy/lvz5G2L1bMczt43v0PWjrXFHNFeJzjA18MSNjARBBsnq2elGBg9enSsjKUzsJzbDEtYkYsVCaCioiJWZkWh8FJWVhYrO3nyZKwsZD+wdAYsNUdSrP3AoiOwtbOEV0xowwQUXqEIK1cqByGEEAWBjJAQQojUkBESQgiRGjJCQgghUkNGSAghRGrkrTpuyJAhWaooS+nBlDZeNZelRPMeHxKiJqnqjBESYofNX4gSj8HUYCG5WrwhdkJCiiRRS1rHexV3FkzhxRRKFqwu6z9TbbEyILkSjhGS/4bhVSZa/WR7hynhQq47pgZj62mpEFn7jN7eXlcZwMcfki/NOyfeXEqsLanjhBBCFAQyQkIIIVJDRkgIIURqyAgJIYRIjbwVJuRiOXK9DvcQR7LXOW7B+sr66Q3lA4SJEJLgDekB+HM5WbD+e3PyWPVY7h0GE1AA3GnL1m4wnPAWbE6t/nvrsXX2nhPgIXa8TnhrP3nzRrHwRFZdRkiIHTb3XmEAwJ37THDgDc1ktRUSmsp7L/lD3XP0JCSEECI1ZISEEEKkhoyQEEKI1JAREkIIkRp5K0zIdYpZEROYM5U55EKEBcwhF5K7xxtJIOTNbZa/JkSA4X3zm2GJANiahIzT+0Y2az8kMoRX7BBaN5cQsUJIBA3WJ1Y3ZOwszw7bY9YeOXHiBC33YF03hw8fjpWFCF3YeZkIgolXvKIKICw6Aes/EyGw+bTueV4RgSXgYLD7G9vP1n00V+iiiAlCCCEKAhkhIYQQqSEjJIQQIjWCjNCaNWswZcoUVFRUoKKiArNmzcKzzz6b+T6KIjQ1NaG2thalpaWYO3cuduzYcd47LYQQ4sIgyAiNHz8ejzzyCF555RW88sor+MIXvoA/+ZM/yRialStXYtWqVfiHf/gHvPzyy6iursa8efPQ19c3KJ0XQghR2BRFCZPajBo1Cn//93+P73znO6itrUVjYyMeeOABAB+qM6qqqvDoo4/i7rvvdp2vt7cXlZWVGDZsWJbaJUT15VWPWCodrxLOUq+wkChMacLOaYVOYSE82NhDchwxrJAqXphyiOWuAbiK0Jtnx1JtMYVXiFLHq1oLUQ559561dt59wsrGjx9PzzllypRYGVN4WaovNv9McccIUbyF1GXj94aZsa47FuKHraelrjt+/HisbOfOnbEydi1Y4YXYmLzKQIDPqTcEl3c+z549i66uLvT09NAQT1nndJ2RcObMGWzatAnHjx/HrFmz0NHRga6uLsyfPz9Tp6SkBHPmzMGWLVsG2owQQogLmOD3hLZv345Zs2bh1KlTGDFiBJ5++mlce+21GUNTVVWVVb+qqgrvvPOOeb7+/v4sPbuVTVAIIcSFR/CT0KRJk7Bt2za89NJL+O53v4u77ror6/Ey97EwiqKP/YmopaUFlZWVmU9dXV1ol4QQQhQowUZo2LBhuOqqqzB9+nS0tLTghhtuwA9/+ENUV1cDALq6urLqd3d3x56OPsqyZcvQ09OT+XR2doZ2SQghRIGSOGxPFEXo7+9HfX09qqur0draiqlTpwL40NnW1taGRx991Dy+pKSEOt2HDBnicrIzh5o3d48VZoU5KZPmlGF1Wd/Hjh1Lj584caKrHeunTxYSxRveyBveBwDKy8tjZZaDlIkIvOGFrLxBXhFCiCiFOWPZfggRFoTA2md7lO2nI0eO0HO+//77sbJzf0h+lJA8OWxO2Hxa+4EJWFjdELECg4kFLIe7V2xhCRPefvttV/tsTNY4vcIrS2zByr3il5B7gZcgI/TQQw9hwYIFqKurQ19fHzZt2oQXXngBzz33HIqKitDY2Ijm5mY0NDSgoaEBzc3NKCsrw6JFi857x4UQQhQ+QUbowIED+OY3v4n9+/ejsrISU6ZMwXPPPYd58+YBAJYuXYqTJ09iyZIlOHLkCGbOnInNmzfTv46FEEKIICP04x//+GO/LyoqQlNTE5qampL0SQghxEWCYscJIYRIjbzNJzR06NAsZ1nIW+/MQcscb9bb4Mzx532T34KJL0aMGBErmzZtGj3+i1/8oqud119/nZazF4Y7OjpiZWyeQ+aJOaeZAAHwO1ND3oRn5WxMltM3yZvjVvARVh4SnYDB5jlEPNPd3R0rY/M0atQoerz3zXl23VnXMnPYM6xcRix/ztGjR13ntObp0KFDsbJcBTBgO+y9OX1YPeuew/YTi7gQEtHFK56x9miSwDt6EhJCCJEaMkJCCCFSQ0ZICCFEasgICSGESI28FSbkOrosR6j3DXdvmQVzjlsO1pBICrlYkQBuueWWWBkL0/9f//Vf9HgmWKipqYmVvffee7Eyy4nvfXvacpB6HfYhzm1vtAvrbXJv2gZWz+oT22deAYRV1wtzWAPcEc7e+rfWzuvI9l6fVl0mVrD2XXt7+4Dbt87pjc4Q4phnc+/d9xYhaV3YWL173LtHQ/quJyEhhBCpISMkhBAiNWSEhBBCpIaMkBBCiNSQERJCCJEaeauOy8VSn3gVbixsTgheRcnHlefClEcslA/Ac60wrrvuOlrOwq+w0C1MNWaFU2HjZPMUohrz5jiy1G0s/wwLGxQSBsqrfApRW7JzWsczhRsbkzecC8DzDLHjWR4qgK/9yJEjY2UVFRWxst7eXnpOprxiIXqsHElsrCHr7IXNk6WuS9J+iOIuRG3pvT+FqHxz2woZt56EhBBCpIaMkBBCiNSQERJCCJEaMkJCCCFSo2CECVbokrKyMlddr2MfAPr6+lz1LEcyExx420+at+iyyy6j5V/4whdiZSzMCcPquzf/izVPXscnCwFiOV2t3EVJ8IbyCQmTwrBEBJYIIxfWT8u5zdbOEsUw2JiYiGDXrl2xspCQLkxQZO07dt0zoQq7xixHutfBbu1lr6CJhfJhfQf8udGShHuysMaZu3clTBBCCFEQyAgJIYRIDRkhIYQQqSEjJIQQIjXyVpgwdOhQlwOTRQIYN25crIw5OJkzEACOHj0aK2O5VliZBXMQM4ez5Zz2YkWGYG0xR3SIY5+tT0jEBIY3b5PldA3JPZQE1o4196x9JqzwChAAPs+sTyG5ew4cOOBun8EELGycIXucOeettWeCIiZCYMIhSxAUco0zvAIWr3jFgo3J2o+sLlsT1vckudIs9CQkhBAiNWSEhBBCpIaMkBBCiNSQERJCCJEaMkJCCCFSI2/VcaWlpVnKHiukyKxZs2Jl3twalmpq//79sbL3338/Vnbs2DF6PGufqU9Ccq289957sTIWosdS/I0dOzZWNmbMmFjZm2++SY9nsDGFhAoZDNUaI0R55A1/wtSO1njY8UnHzhRWITmKmEKKEZIjiYXTCcnlxNpi/bTWk6kL2fXAVGPe+QD43IeE7SktLY2Vsb5bffLuUet4b//Z8VYYqNz2Q0Iz6UlICCFEasgICSGESA0ZISGEEKkhIySEECI18laYcOWVV2Y566qqqmg95tBjzlDm9LQcpOx41g4TKwDcGZk0z4039EuII9mLFbqEOTNDRADs+BDnuhfmCLYcrAy29szxGuLcDpk7b54gNk9W3iUWYifEmezNk8P2bUjOLDan1pgYrE8s71FIyCSGJQhi1z0LRRQiAmAwkZA1JrYm3hxF3lBAyickhBCiIJAREkIIkRoyQkIIIVJDRkgIIURq5K0woaamJsupyJzLVjlzBjJHquUg9Tr8Lecbc955nalWn5jjMcT5x3KtHDp0yHVOyxnJBAveaBUWbPwh+We8znXL6Ruyzl68ERMsRzLbu97IFEyAENK+JbZgDn/vOlnjZGsXsncYLNIKExFY7XjXzhLPePMRsf1o7WXvfrTWwysIShKFQREThBBCFAQyQkIIIVJDRkgIIURqJDJCLS0tKCoqQmNjY6YsiiI0NTWhtrYWpaWlmDt3Lnbs2JG0n0IIIS5ABixMePnll7F27VpMmTIlq3zlypVYtWoV1q9fj4kTJ2LFihWYN28e2tvbUV5e7j5/aWlplpPaEiYwvG/th7zhzhzmlZWVtC4Lac+cfFYqCC/WW9oMFt3hyJEjsTLmUGRvmAN8TGzuQ95G947JEhZ43/wOcZwyQsQKrC1vKgaAO5LZ8SFpE7wiBGuevNcYa99ymDPnfojQhR3P9u7IkSNjZdZ4vJEtrHn2zlPSqCAhkSnY/FupKLzk7t2QaA8DGvmxY8dw5513Yt26dVk5baIowurVq7F8+XIsXLgQkydPxoYNG3DixAls3LhxIE0JIYS4gBmQEbrnnntw++2347bbbssq7+joQFdXF+bPn58pKykpwZw5c7Bly5ZkPRVCCHHBEfxz3KZNm/D73/8eL7/8cuy7rq4uAPFgo1VVVXjnnXfo+fr7+7N+grEyiwohhLjwCHoS6uzsxH333Yef/OQnHxsVOvd35CiKzN+WW1paUFlZmfnU1dWFdEkIIUQBE2SEtm7diu7ubkybNg3FxcUoLi5GW1sbfvSjH6G4uDjzBHTuiegc3d3dZiqGZcuWoaenJ/Pp7Owc4FCEEEIUGkE/x916663Yvn17Vtm3v/1tXH311XjggQdw5ZVXorq6Gq2trZg6dSqAD5UYbW1tePTRR+k5S0pKaFiYY8eOucL2MPWJV5lhKVK8IVEsmPqEKY+YIsWSs2/atClWdvPNN7v79Nvf/tbVJ4Y1T14lnNVOSN1crCfrpCFyWPtMZRSy77yhgEJyMbFrhoWIscL2MELCtLDrkak92S8mljrOO88h4Y3YNcYUmFZoKm+4r6NHj9LjvfcSVs/aT6w8JEeTN5QRw6sKDVGPBhmh8vJyTJ48Oats+PDhGD16dKa8sbERzc3NaGhoQENDA5qbm1FWVoZFixaFNCWEEOIi4LwHMF26dClOnjyJJUuW4MiRI5g5cyY2b94c9I6QEEKIi4PERuiFF17I+n9RURGamprQ1NSU9NRCCCEucBQ7TgghRGrkbT6hgwcPZjkgLWfm6NGjY2XMGRviuGOOZBYqxHLasrrMkc6cd3v27KHnZHXb29tpXcbevXtjZQcPHoyVsTFZTkuvAMQKs8KO9zrxQ8LuMEe21XevWII5vEPCQLFxhoQiYg5zdk4WQgrg1wjrv7V27HpkDm9Wz7oW2fiZYCAkXBWbE7bGVggtVtebRwvg/Wf7OSRkkve6s/rE1pQJTdje8eZ3ChEm6ElICCFEasgICSGESA0ZISGEEKkhIySEECI18laYsHv37iynYk1NDa3HHGpJ33BneXbYG9HMQWnB2grJtbJr165YWUgOEHbekPYZSfLcWHW9uYdChAkhwga2TqxPzOFtRZZg7bN2QsbkfRPf2iOnTp1ytR8SPYTtHa8gB+C5f6xIBoyPi2f5SViRJdg8Max+evMEhUSrYLD9ZN3f2L2QrZ1XoGXV9aInISGEEKkhIySEECI1ZISEEEKkhoyQEEKI1JAREkIIkRp5q47r7+/PUtYcPnyY1mOqsTFjxrjasJQv+/fvd9W1lCLe0BYMS9HC1DMsfEmIwoodH6KGYionpla0FHdMUcP6z8qSzDEAM6q7VyUUkgvJq1yyFEbeNQ0JJcTaYsdbOY7YPvGG6AnJBcXwKihDCJl71s+Q684799YeZ6pcdrx13TElnzeXVRIVnHnO835GIYQQwomMkBBCiNSQERJCCJEaMkJCCCFSI2+FCWfOnHEJE3p6emJlfX19rjYsZxxz/DEnvBV+xOs0Z85pK9cKO2dZWVmszHJGMmcuc1CGhOpImuuF9XUwwvawebJCLjEHrzf/i9V3Fo6GhZgJybvkDdlk7VG2zqyfbO4ALtRJIjQBwkL0JIGJUiyREsuR5HXiA3z+mbAhRGjDxD8hsL3L5p5dnyE5r7zoSUgIIURqyAgJIYRIDRkhIYQQqSEjJIQQIjXyVphw4sSJLGeX5bRkTsKDBw/GypjD33Liex2PloPQ66ANgbXFnOvMkQrwMXmFBdZb0qwuc3pab8IzZyxz7ofMndfBaglAvPljGCHCAkZItApvdANr7tg6efcY4O9r0kgCzLFvCUBYW1aeoFyqqqpc9QC+R44dO+Y+nuUmY3239iKbJ0tAwmD7ke2HkOgIuef07nlAT0JCCCFSREZICCFEasgICSGESA0ZISGEEKmRt8KEkpKSLGed9ea3983xkLd/ve1YfWJvw1dUVMTKvCknAO6kZMIAy5HMnIxesYIl4GAMhnM7BG8UCmtM3j4xEUJIGg62dywn/mCkcmDrxPZYiLDAEnt4Yftx5MiRsTJLfOPtKxM2sOsT8Asb3nnnHVrO5nTUqFGxMnaNWONh131IxAVvVJKQSB25e9y6NzL0JCSEECI1ZISEEEKkhoyQEEKI1JAREkIIkRoyQkIIIVIjb9VxQ4YMcaldQnJ75JI0NwZTwQFcJTR79mzXOUPyCTH2799Py5l6h4UaCVHZMJjqzJpPpqBhyh8WkiQkdEvIHvEqgljfvUrNkLYBv2IvRN3G5pntZ0tdx+bfquuFKeGYWtO67mpra13Hs7WzQtR499NVV11Fj2fz3NXVFStjc2fNJ9sPIeGyWF2290LC9iRBT0JCCCFSQ0ZICCFEasgICSGESA0ZISGEEKmRt8KEXELCQCQRK1iEOOmuueaaWBlz5DJHrOVwt5yxuVRWVtJylsOEjen48eOxMms+mYiB1bUc9t5cMd48MwB3JIeE2GHlrIyFcwmZJ4YlIvCGw2F7xMpJw8QezIkeIgBhjnBvKB6Ah86prq521bP6xCgvL3fVA/jasbmz1pjNH1snJqCw9hMrZ9eDFZoqaW4zRu74FbZHCCFEQSAjJIQQIjVkhIQQQqRGkBFqampCUVFR1uejv9lGUYSmpibU1taitLQUc+fOxY4dO857p4UQQlwYBAsTrrvuOvzyl7/M/P+jzsiVK1di1apVWL9+PSZOnIgVK1Zg3rx5aG9vD3IGMkLyCQ2G4y0k/wuDOWPHjh0bK7Oc+CzfCHNQjh49mh4/Y8aMWNnrr78eK9u7d2+szBona585py3HOqvrfRM/5O38kLxF3jVl7YdETAiJTMH67z3eErQwEQLDmg8m1mBrxxzulnjGGx3BEpWw87J5YvWsnFfMue/NDwXwvE1VVVWxMnZ/sP6AZ3uPCVCs645dt0kFQUkI/jmuuLgY1dXVmc+5G2kURVi9ejWWL1+OhQsXYvLkydiwYQNOnDiBjRs3nveOCyGEKHyCjdDu3btRW1uL+vp6fO1rX8OePXsAAB0dHejq6sL8+fMzdUtKSjBnzhxs2bLFPF9/fz96e3uzPkIIIS4OgozQzJkz8cQTT+D555/HunXr0NXVhdmzZ+PQoUOZoHy5j5pVVVU0YN85WlpaUFlZmfnU1dUNYBhCCCEKkSAjtGDBAnz5y1/G9ddfj9tuuw0///nPAQAbNmzI1Mn9DTmKoo/9nX3ZsmXo6enJfDo7O0O6JIQQooBJJNEePnw4rr/+euzevTujkst96unu7qaOuHOUlJSgoqIi6yOEEOLiIFHYnv7+frzxxhv4oz/6I9TX16O6uhqtra2YOnUqgA+VJW1tbXj00UeDz3369GmXUompX6xQI0lgShGrHaY+8arbrFAdXjWWdTxT3zDFIptPax28eXYGQ1FjKd68/Q9RNrJzhijhvMpKFg4mBNZO0vxQ1n5iqjXvmFjII4CrRdl1N2rUKHr8wYMHY2VjxoyJlbExMRUb4N+7lhLNCp2TCxuntR9YaK2Q/ezduyGhgHIViyHXfNDd+m/+5m9wxx134PLLL0d3dzdWrFiB3t5e3HXXXSgqKkJjYyOam5vR0NCAhoYGNDc3o6ysDIsWLQppRgghxEVCkBF699138fWvfx0HDx7E2LFj8bnPfQ4vvfQSJkyYAABYunQpTp48iSVLluDIkSOYOXMmNm/enPgdISGEEBcmQUZo06ZNH/t9UVERmpqa0NTUlKRPQgghLhIUO04IIURqFEw+oRCYUyxEWMAIcUQzB+l7770XK2NOYyvMitdpbf30eeTIEdfxbJyWMzLpnLJ1YiFZvHlqAP86WY5cVs7G6XU4W8eHiAhYn5hzOiQ8kTdkUkjYH2/oFyufEGuLHd/T00OPZyIE1k+mwLXC9oSE+GGwUER9fX2xshBHPtvjIWGsGGxMI0aMcNUD4vedEEGMnoSEEEKkhoyQEEKI1JAREkIIkRoyQkIIIVIjb4UJQ4cOHXBeIG+uE+v83pw2lnOcOU5Zvg9vXhCAO5KZCMErQAC4c5uNyXIyeucpaQSLkKgYrP/MuR0Ccy6HRKtgTueQ/cicweycIcIENqchzuTBcI6zeQ5ZT69znQkDLOFPiADFCxNgeKOsWITcK9k6sXk6duxYrCxkj3nRk5AQQojUkBESQgiRGjJCQgghUkNGSAghRGrkrTAhF8sZyRx6zOnLHIzW2+Be53qI4/BcGvSPcuDAgVjZpEmT6PEsVPz+/ftjZZYjlYkQ9u7dGytjzmkm9AC4iCKpCIG1FSIs8LZvOeGtkPy5hDjMkwojvM7gkHaSRoHwrj07pxXxgEUnSMqJEydiZey6Z054wL8fLNg8sfUMiaBhCWBysfYDGz+7lzGxg3UvyL1nhkSA0JOQEEKI1JAREkIIkRoyQkIIIVJDRkgIIURqyAgJIYRIjbxVx509ezZLnRESUoTVZYoU65xMHcfUHlaoDKaIYSqhQ4cOxcqYmgdIrjpjeEP0hKiu2NxZ4Vy8Y2LtW3NvqXdysRRnbJ1YOJmQEDWsLgsTE6JOC8mxxGBjYkowlo8H4AorNk62nzs6Oug52dqNHj06VmbtR5YniI2TXcuWmsu6Hr2w87JzWuo8hle1Zs0Tuz+VlpbGypiidjDQk5AQQojUkBESQgiRGjJCQgghUkNGSAghRGrkrTAhF8vJ5nVEMye4dSxz/IWEaWG5VpiDkh1/8OBBek7miA4RKzBHMnM8snYsEUCI2IPBHNls7pIS0qckYVpCxAps7pkTPQQ2zoHm5DqHlWeHOddZXe++B7jDvLe3N1Y2cuRIejyry8pYHi6rTyEiBgYTdrAQOSyElwUTsISE/WFj9YbtsVDYHiGEEAWJjJAQQojUkBESQgiRGjJCQgghUiNvhQlDhgzJcox5BQjng6RtseNZWYjzjjm9mSPXcm6HvE3vJamIwBuJgfWdveENcEcwE1BYERPYmJgjmDl9rfX0RnywHMmsrrfMwpszyxrTiBEjYmXe3D3WOQ8fPhwrO3r0aKysr6+PHs/yETGhSUhUDya2YKISK7IC6yu7F7DjrXliezREFJPk/mbtsdzrMUQMpCchIYQQqSEjJIQQIjVkhIQQQqSGjJAQQojUkBESQgiRGnmrjvvggw+ylBhWiBqv0oMprCx11x8qnExQaAuisPLmKrFgSjqvsi8Ea+3YmJiqhrVv5blhY/Iq5oBkYVpCchyxfoao41ifQs7J8CrmrLpMicYUnFZoJO/etdaO5eTxKjCtXE4snA1TZrJ6AFcH9vT0xMrYPLO5A4Dhw4fHytj9zdqPrJxdI977AxBfO4XtEUIIURDICAkhhEgNGSEhhBCpISMkhBAiNfJWmJAbtsdydHlDjTAHpRXKhokQQoQNXqccc+5aTldv+5aD1Jsnh/XdcnB6Q4VYzu2QtrwwB2tIiBxvTh7Wd8tpy5zTDGs+2dp5RR0hAgyrLoPtRzZ+b24uwH/dsVA+AO+/V1BkCV0YTABhzR0TIbB5Ytcty3sE+AUcIYIibw40LyFt60lICCFEasgICSGESA0ZISGEEKkRbITee+89fOMb38Do0aNRVlaGz3zmM9i6dWvm+yiK0NTUhNraWpSWlmLu3LnYsWPHee20EEKIC4MgYcKRI0dw00034fOf/zyeffZZjBs3Dm+99RZGjhyZqbNy5UqsWrUK69evx8SJE7FixQrMmzcP7e3tpqONkevYst589ooQmKPMOid7e5o5hy3HXZK37i2HHnt7mTmyWf4TwO8g9uZfGSyYg5gJGyxHckj+GobXOc/qhYgqQhy3IYIDz7EAn1OvMMCqy5zrbO7ZG/8Ad7izebL6ZOWYyoX13VoPNn+DcT2wvWNFTGD9Z9dDyB5jdUMix+SuScg1F2SEHn30UdTV1eHxxx/PlF1xxRWZf0dRhNWrV2P58uVYuHAhAGDDhg2oqqrCxo0bcffdd4c0J4QQ4gIn6Oe4Z555BtOnT8dXvvIVjBs3DlOnTsW6desy33d0dKCrqwvz58/PlJWUlGDOnDnYsmULPWd/fz96e3uzPkIIIS4OgozQnj17sGbNGjQ0NOD555/H4sWL8f3vfx9PPPEEAKCrqwsAUFVVlXVcVVVV5rtcWlpaUFlZmfnU1dUNZBxCCCEKkCAjdPbsWXz2s59Fc3Mzpk6dirvvvht/+Zd/iTVr1mTVy/19M4oi8/fyZcuWoaenJ/Pp7OwMHIIQQohCJcgnVFNTg2uvvTar7JprrsGTTz4JAKiurgbw4RNRTU1Npk53d3fs6egcJSUlrpDhlpPN66D1hnQHwkQIXpKmgmDjZ85la57YHwGsT0yUkbTvlnPcmw6A9YntGYA7t9k5rX3D5o8d740OAPBxhji3k0Q3sPYDc+4z5/aIESPo8d639tneOX78OK3LBAusbtDb+OS6Zw5/az1CUmEw2HnZenojmlh9Shp9xXt/sUQhuXUHLZXDTTfdhPb29qyyXbt2YcKECQCA+vp6VFdXo7W1NfP96dOn0dbWhtmzZ4c0JYQQ4iIg6Enor/7qrzB79mw0Nzfjz/7sz/C73/0Oa9euxdq1awF8+JdgY2Mjmpub0dDQgIaGBjQ3N6OsrAyLFi0alAEIIYQoXIKM0IwZM/D0009j2bJl+MEPfoD6+nqsXr0ad955Z6bO0qVLcfLkSSxZsgRHjhzBzJkzsXnz5qB3hIQQQlwcFEVJczefZ3p7e1FZWYmhQ4dm/cZu+XSsCM25JI3OnNQnFBKhmMHGHzImdrw3snhSn5C1dkl8QtZv6OyFSVbXGhOb07R9Qmz+vGsScnmzPZ7UJxTiV/D6hCzYi9reF3Dz0SfkvbcB3M+V1CfEjrfmifmE9u3bh56eHlRUVNBjzqHYcUIIIVIjb/MJ5WI9iXj/SmZ/pVp/JXpDWFh/+bK/INhfs96QQ1ZbrJ/WmELyKeVi/TXI+sTGbq2d9+nOCkXEGDVqVKyM5X+xYGF/mGqM/YVt/ZXI5pmN01p771N0yB73Ku6suWN1WVts71hhe1ifWCgeaz95Q1N51wPga+r9VcHCWzdpuCnr+vaG5mL9DFHxedGTkBBCiNSQERJCCJEaMkJCCCFSQ0ZICCFEauStMOHs2bMuiTaDOeSsMC+MEBECgzmtvY7gELEE65PlzPQ6Hlk71jmTOim97Yfk0/GuvTUmJnVlUtkQUQlrPyREjjdPT4jD3LufrXpep7k3bA4wOE5v7ysHbI6tPoXsR68Un9WzJNpsTCFScrb32DolyZs0aGF7hBBCiPOJjJAQQojUkBESQgiRGjJCQgghUiNvhQm5WE465pBjdZPGgArB69xPkifGOt5yJCcZf0gMK0aIqMQb68yb18Q6pzUfSWP8MZgjmIkVLIe9lxDxDBsnmxNrPZiIImn/vdFPLAEDizPH5pmJEELuLyEx1byExNhLei9j/fe2770XSJgghBCiIJAREkIIkRoyQkIIIVJDRkgIIURqyAgJIYRIjbxVxw0bNsyl9mFKD6ZGSqp6Yn2xQgElUa+EqL5CcoiwvCxMJcTGlDT5rtUnFj7Fm/fIUkh5VTnWfmBr5+0nU3cB/pBJSVWIbN+HqL4Y1tp7M3mydkJCCYVk9fWG5mI5o6z58CptrXtVkqy41nWTJL9USFveHGisT0FZn901hRBCiPOMjJAQQojUkBESQgiRGjJCQgghUiNvhQnefELMcRrizPQS4sz05o8JCbvDnNvseCZAAPwihJBcKV7BgjUmJi5gDm9WLyTXSkjeJTZWr1giaeiWEAFISCgihvcaseqxOWHts7Wz9kPSHEch4aGSwPZISC4k7z6x5v7YsWOxMnY9hOzHkGuEkUT4pSchIYQQqSEjJIQQIjVkhIQQQqSGjJAQQojUyFthQlFRUZazzHLaModa0jf8vW9JW844JgJgjkvm+LOcy2ycXse+Vdf7Nrvl4PRGcbDwvnkekqcmqdiCrQkTlTBCojB4HfsW7PiQt9S9WNeSNxcW66flxGcRJ/5QecBCRA0hkS3Y/HlFBNZ+YrmcGFYED+/1wMQ31rWQu/eUT0gIIURBICMkhBAiNWSEhBBCpIaMkBBCiNTIW2HCkCFDspxdlpPOCnfuwXK6Michq2s5WJnjkTnqBiOcvwWbJ/ZGdkjaBEaIIzlJhAErbD8ThVhRJBhsTZK+ic+ibSQVEXgdv0lFOhZeAUrI3mEOd+ZcD3F6M9g1Zjn72TXivW4AoLe319WnkSNHuuoBwIkTJ2JlTLwTEhXEex8dDPGLnoSEEEKkhoyQEEKI1JAREkIIkRoyQkIIIVJDRkgIIURq5K06LjefkKXG8SpVvHlmPq6t802I6soKweHFG+ojaV4RRkguKG9bfX19tLyiosJ1fMiYvAqzkH3jDQ1lkVQd51VhhoSRYm0x1VdtbS09p1dJt3//flp+4MCBWBmbJ6ZWtNRpTIU5fPjwT+jh/8HuT16FmXXNs3tZR0dHrIyp6Kzjk5K79iGqTD0JCSGESA0ZISGEEKkhIySEECI18s4ndO63xCS/MbK6SY9PUu98HJ+0rSQ+hMEaJ+tT0rn3jjPEJ+T9DT/kbXLWfkifkvrpks6Td+1YVIykPgkr0gbzX7F+hvSJ+TND/LNsTpL6hFj/WVnI2nnxnvPc/z3Xc1E0WHE9Bsi7776Lurq6tLshhBAiIZ2dnRg/fvzH1sk7I3T27Fns27cP5eXl6OvrQ11dHTo7O92qp3ynt7dXYyoALrQxXWjjATSmfCaKIvT19aG2tvYTVcB593PckCFDMpbz3GNrRUVFQS8IQ2MqDC60MV1o4wE0pnylsrLSVU/CBCGEEKkhIySEECI18toIlZSU4OGHHzZzxxQiGlNhcKGN6UIbD6AxXSjknTBBCCHExUNePwkJIYS4sJEREkIIkRoyQkIIIVJDRkgIIURq5LUReuyxx1BfX49LL70U06ZNw29+85u0u+TmxRdfxB133IHa2loUFRXhpz/9adb3URShqakJtbW1KC0txdy5c7Fjx450OuugpaUFM2bMQHl5OcaNG4cvfelLaG9vz6pTaGNas2YNpkyZknkxcNasWXj22Wcz3xfaeHJpaWlBUVERGhsbM2WFNqampiYUFRVlfaqrqzPfF9p4zvHee+/hG9/4BkaPHo2ysjJ85jOfwdatWzPfF+q4BkSUp2zatCm65JJLonXr1kU7d+6M7rvvvmj48OHRO++8k3bXXPziF7+Ili9fHj355JMRgOjpp5/O+v6RRx6JysvLoyeffDLavn179NWvfjWqqamJent70+nwJ/DFL34xevzxx6PXX3892rZtW3T77bdHl19+eXTs2LFMnUIb0zPPPBP9/Oc/j9rb26P29vbooYceii655JLo9ddfj6Ko8MbzUX73u99FV1xxRTRlypTovvvuy5QX2pgefvjh6Lrrrov279+f+XR3d2e+L7TxRFEUHT58OJowYUL0rW99K/rtb38bdXR0RL/85S+jN998M1OnEMc1UPLWCN14443R4sWLs8quvvrq6MEHH0ypRwMn1widPXs2qq6ujh555JFM2alTp6LKysron/7pn1LoYTjd3d0RgKitrS2KogtjTFEURZdddln0L//yLwU9nr6+vqihoSFqbW2N5syZkzFChTimhx9+OLrhhhvod4U4niiKogceeCC6+eabze8LdVwDJS9/jjt9+jS2bt2K+fPnZ5XPnz8fW7ZsSalX54+Ojg50dXVlja+kpARz5swpmPH19PQAAEaNGgWg8Md05swZbNq0CcePH8esWbMKejz33HMPbr/9dtx2221Z5YU6pt27d6O2thb19fX42te+hj179gAo3PE888wzmD59Or7yla9g3LhxmDp1KtatW5f5vlDHNVDy0ggdPHgQZ86cQVVVVVZ5VVUVurq6UurV+ePcGAp1fFEU4f7778fNN9+MyZMnAyjcMW3fvh0jRoxASUkJFi9ejKeffhrXXnttwY5n06ZN+P3vf4+WlpbYd4U4ppkzZ+KJJ57A888/j3Xr1qGrqwuzZ8/GoUOHCnI8ALBnzx6sWbMGDQ0NeP7557F48WJ8//vfxxNPPAGgMNcpCXkXRfuj5CZ/iqIoKHFYvlOo47v33nvx2muv4b//+79j3xXamCZNmoRt27bh6NGjePLJJ3HXXXehra0t830hjaezsxP33XcfNm/ejEsvvdSsV0hjWrBgQebf119/PWbNmoVPf/rT2LBhAz73uc8BKKzxAB+mq5k+fTqam5sBAFOnTsWOHTuwZs0a/Pmf/3mmXqGNa6Dk5ZPQmDFjMHTo0JjV7+7ujv11UIicU/cU4vi+973v4ZlnnsGvf/3rrGRVhTqmYcOG4aqrrsL06dPR0tKCG264AT/84Q8Lcjxbt25Fd3c3pk2bhuLiYhQXF6OtrQ0/+tGPUFxcnOl3IY0pl+HDh+P666/H7t27C3KNAKCmpgbXXnttVtk111yDvXv3Aijca2mg5KURGjZsGKZNm4bW1tas8tbWVsyePTulXp0/6uvrUV1dnTW+06dPo62tLW/HF0UR7r33Xjz11FP41a9+hfr6+qzvC3FMjCiK0N/fX5DjufXWW7F9+3Zs27Yt85k+fTruvPNObNu2DVdeeWXBjSmX/v5+vPHGG6ipqSnINQKAm266KfZ6w65duzBhwgQAF8615CYtRcQncU6i/eMf/zjauXNn1NjYGA0fPjx6++230+6ai76+vujVV1+NXn311QhAtGrVqujVV1/NSMwfeeSRqLKyMnrqqaei7du3R1//+tfzWoL53e9+N6qsrIxeeOGFLLnsiRMnMnUKbUzLli2LXnzxxaijoyN67bXXooceeigaMmRItHnz5iiKCm88jI+q46Ko8Mb013/919ELL7wQ7dmzJ3rppZeiP/7jP47Ky8sz94FCG08UfSifLy4ujv7u7/4u2r17d/Rv//ZvUVlZWfSTn/wkU6cQxzVQ8tYIRVEU/eM//mM0YcKEaNiwYdFnP/vZjBy4EPj1r38dAYh97rrrriiKPpRhPvzww1F1dXVUUlIS3XLLLdH27dvT7fTHwMYCIHr88cczdQptTN/5zncy+2vs2LHRrbfemjFAUVR442HkGqFCG9O592MuueSSqLa2Nlq4cGG0Y8eOzPeFNp5z/OxnP4smT54clZSURFdffXW0du3arO8LdVwDQakchBBCpEZe+oSEEEJcHMgICSGESA0ZISGEEKkhIySEECI1ZISEEEKkhoyQEEKI1JAREkIIkRoyQkIIIVJDRkgIIURqyAgJIYRIDRkhIYQQqSEjJIQQIjX+HyyhMwk7XUXYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "denoised_median = filters.median(image3, morphology.disk(1))\n",
    "\n",
    "plt.imshow(denoised_median, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "40c7aa53-5352-4b16-b513-fa97d7fd81d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d868ca7af0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "denoised_median2 = filters.median(image3, morphology.disk(5))\n",
    "\n",
    "plt.imshow(denoised_median2, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "523a8cff-29b3-469a-8f09-4e466ef85de5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d869d0c430>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "denoised_gaussian = filters.gaussian(image3, sigma=1)\n",
    "\n",
    "plt.imshow(denoised_gaussian, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b353e7d-049d-4d12-b8d9-05f24f5c43bd",
   "metadata": {},
   "source": [
    "We can also show these images side-by-side using matplotlib."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9e3765fb-b91d-4f34-a895-5c957b12af82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d868ba6970>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x1500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1,3, figsize=(15,15))\n",
    "\n",
    "axes[0].imshow(denoised_mean, cmap='gray')\n",
    "axes[1].imshow(denoised_median, cmap='gray')\n",
    "axes[2].imshow(denoised_gaussian, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65a83ca8-d768-4cf2-8e6c-d1dc56fdde59",
   "metadata": {},
   "source": [
    "### Top-hat filtering / background removal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7de80baa-591a-4ece-900d-2b4522f45cf7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d869db3640>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_hat = morphology.white_tophat(image3, morphology.disk(15))\n",
    "\n",
    "plt.imshow(top_hat, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19ecb69f-011c-4e9b-997d-aca16457e790",
   "metadata": {},
   "source": [
    "### Edge detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f615fef7-0596-45bb-b5da-c47e61bfa7cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d869de9dc0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sobel = filters.sobel(image3)\n",
    "\n",
    "plt.imshow(sobel, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e0f84ee-ca0e-4509-a2ab-f0c46355cf9b",
   "metadata": {},
   "source": [
    "## Custom kernel"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c45abd8-03a6-4cea-ac06-06b956ca0e61",
   "metadata": {},
   "source": [
    "When applying linear filters such as Gaussian and Laplacian, we technically [convole](https://en.wikipedia.org/wiki/Convolution) the image. We can also convolve it using a custom kernel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5a332f51-9178-4742-a581-979ffec364cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "kernel1 = [[1, 2, 1],\n",
    "           [0, 0, 0],\n",
    "           [-1, -2, -1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6b03afb7-200f-459b-9889-4aaacb4a03a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d869e720a0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "output1 = convolve(image3, kernel1)\n",
    "\n",
    "plt.imshow(output1, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99c1fb79-869c-43a4-8328-c344751fba0e",
   "metadata": {},
   "source": [
    "# Exercise 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc5c18a9-76a3-45a1-92e6-5578d80f9148",
   "metadata": {},
   "source": [
    "The above filter hightlights horizontal edges in the image. Write code that highlights vertical edges. \n",
    "\n",
    "Hint: [read more about the Sobel operator](https://en.wikipedia.org/wiki/Sobel_operator)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b86a44af-2000-4e1e-a074-0505465dadbe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "cd1df487-ec79-4bd9-b714-bbe9ecd8970f",
   "metadata": {},
   "source": [
    "# Exercise 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb883343-6579-436c-a4a6-39c2fb73cf4e",
   "metadata": {},
   "source": [
    "Write a function that computes the [Difference of Gaussian](https://en.wikipedia.org/wiki/Difference_of_Gaussians). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3c396772-1f11-4fb7-a00c-aee12610fb7d",
   "metadata": {},
   "outputs": [
    {
     "ename": "IndentationError",
     "evalue": "expected an indented block (1176923579.py, line 3)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  Cell \u001b[1;32mIn[22], line 3\u001b[1;36m\u001b[0m\n\u001b[1;33m    # enter code here\u001b[0m\n\u001b[1;37m                     ^\u001b[0m\n\u001b[1;31mIndentationError\u001b[0m\u001b[1;31m:\u001b[0m expected an indented block\n"
     ]
    }
   ],
   "source": [
    "def difference_of_gaussian(image, sigma1, sigma2):\n",
    "    \n",
    "    # enter code here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2aafb8fd-d63e-4404-a295-67e5f5dc386b",
   "metadata": {},
   "source": [
    "Use a simple function call to try out the function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17829aef-9055-4d64-b717-3ca0cfc4d85b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dog_image = difference_of_gaussian(image3, 1, 5)\n",
    "\n",
    "plt.imshow(dog_image, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "291362c0-db7a-428a-8d12-c952c6c4d3c3",
   "metadata": {},
   "source": [
    "Use the [stackview](https://github.com/haesleinhuepf/stackview) library to play with it interactively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0bb942f6-9567-4d4e-ba7f-03e63aed1f7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "stackview.interact(difference_of_gaussian, image3)"
   ]
  }
 ],
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