Tasks:::
A set of images is given with this assignment to perform the following tasks. However, feel free to use your own set of images.
2.1 Load the set of images and display them as Grayscale and rgb images. You are required to show these images ”inline” rather than creating a new window for every other image. (2 points)
2.2 Implement the function rgbExclusion() in the helper script, in which the input image is decomposed into the three channels: R, G and B and return the image excluding the specified channel. Display the results in notebook. (3 points)
2.3 Take at-least 3 images from given set and plot histograms before and after applying histogram equalization. Show these image inline format i.e. grayscale image –> display histogram –> apply histogram equalization–> display the equalized image and its histogram. (5 points)
2.4 You are required to implement the convolution operation from scratch. This function which takes an image and a kernel and returns the convolution of them. Compare the results of your implemented function with the ones available (built-in) in python packages. You are required to convolve images for sharpening and blurring effects. (5 points)
2.5 Load a couple of images from the given set.
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Apply box filter using convolution, and display the resultant image
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Apply Gaussian filter to the image, with varying sigma values.
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Add Gausian Noise and Salt and Pepper Noise to them.
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Apply Gaussian Filter and Median Filters.
5: Display mesh plots for different i) Gaussian filters, ii) First Order Derivative of Gaussian, iii) Laplacian of Gaussian; using different sigma values
You are encouraged to play with the different parameter values.The results should be displayed in three columns i.e Original Image, Corrupted Image and the Filtered Image. (20 points)
2.6 Load a few images from the given set.
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Apply Sobel operator, computer gradient magnitude and display the results (original image, gradient images and gradient magnitude image).
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Apply Laplacian of Gaussian, computer laplacian magnitude and display the results (original image, filtered images and laplacian magnitude image). Try different filter kernel coefficients.
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Apply Canny Edge Detector and display the results.