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Processing makes it simple to handle images, iterate over the pixels of an image and perform operations on them. here we use OpenCV Tools, OpenCV offers all kinds of algorithms from basic image processing to advanced computer vision

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Processing makes it simple to handle images, iterate over the pixels of an image and perform operations on them. here we use OpenCV Tools, OpenCV offers all kinds of algorithms from basic image processing to advanced computer vision

Image processing is the process of transforming an image into a digital form and performing certain operations to get some useful information from it. The image processing system usually treats all images as 2D signals when applying certain predetermined signal processing methods. We have provided several of the most useful tools here. The codes are written as simply as possible, which helps a lot in learning them.

Before we jump into image processing, we need to first understand what exactly constitutes an image. An image is represented by its dimensions (height and width) based on the number of pixels. For example, if the dimensions of an image are 500 x 400 (width x height), the total number of pixels in the image is 200000.

This pixel is a point on the image that takes on a specific shade, opacity or color. It is usually represented in one of the following:

Grayscale - A pixel is an integer with a value between 0 to 255 (0 is completely black and 255 is completely white).

RGB - A pixel is made up of 3 integers between 0 to 255 (the integers represent the intensity of red, green, and blue).

RGBA - It is an extension of RGB with an added alpha field, which represents the opacity of the image.

Image processing requires fixed sequences of operations that are performed at each pixel of an image. The image processor performs the first sequence of operations on the image, pixel by pixel. Once this is fully done, it will begin to perform the second operation, and so on. The output value of these operations can be computed at any pixel of the image

Image Acquisition Image acquisition is the first step in image processing. This step is also known as preprocessing in image processing. It involves retrieving the image from a source, usually a hardware-based source.

Image Enhancement Image enhancement is the process of bringing out and highlighting certain features of interest in an image that has been obscured. This can involve changing the brightness, contrast, etc.

Image Restoration Image restoration is the process of improving the appearance of an image. However, unlike image enhancement, image restoration is done using certain mathematical or probabilistic models.

Color Image Processing Color image processing includes a number of color modeling techniques in a digital domain. This step has gained prominence due to the significant use of digital images over the internet.

Wavelets and Multiresolution Processing Wavelets are used to represent images in various degrees of resolution. The images are subdivided into wavelets or smaller regions for data compression and for pyramidal representation.

Compression Compression is a process used to reduce the storage required to save an image or the bandwidth required to transmit it. This is done particularly when the image is for use on the Internet.

Morphological Processing Morphological processing is a set of processing operations for morphing images based on their shapes.

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Processing makes it simple to handle images, iterate over the pixels of an image and perform operations on them. here we use OpenCV Tools, OpenCV offers all kinds of algorithms from basic image processing to advanced computer vision

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