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๐Ÿ–ผ๏ธ This repository contains ready to run code for the following image processing techniques: Image Gradient, Image Smoothness, Image Histogram (Intensity Histogram) and Structural Similarity Index Measure (SSIM) of Two Images

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๐Ÿ–ผ๏ธ Image Processing Techniques

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This repository contains ready to run code for the following image processing techniques:

  • Image Gradient
  • Image Smoothness
  • Image Histogram (Intensity Histogram)
  • Structural Similarity Index of Two Images

How To Run

The code is in ready to run condition. Just install the imported modules in Python 3.6 and run the code.

Examples

Below are some images processed using the code given in this repo.

1) Image Gradient

An image gradient is a directional change in the intensity or color in an image. Here Laplacian Gradient Filter is applied to calculate the gradient.

2) Image Smoothness

Smoothing is often used to reduce noise within an image.

3) Image Histogram (Intensity Histogram)

In an image processing context, the histogram of an image normally refers to a histogram of the pixel intensity values. This histogram is a graph showing the number of pixels in an image at each different intensity value found in that image.

4) Structural Similarity Index Measure of Two Images

SSIM is used for measuring the similarity between two images.



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Authors ๐Ÿ‘‹

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Haris Muneer

LinkedIn Link

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Hassaan Elahi

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Contributions Welcome

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If you find any bug in the code or have any improvements in mind then feel free to generate a pull request.

Issues

GitHub Issues

If you face any issue, you can create a new issue in the Issues Tab and I will be glad to help you out.

License

MIT

Copyright (c) 2018-present, harismuneer, Hassaan-Elahi

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๐Ÿ–ผ๏ธ This repository contains ready to run code for the following image processing techniques: Image Gradient, Image Smoothness, Image Histogram (Intensity Histogram) and Structural Similarity Index Measure (SSIM) of Two Images

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