Question: with python ort I (20%): Complete function part1_histogram_compute() to accomplish the following: . Read the grayscale image called test.jpg 3. Plot the histogram. 4. Also,

$with python ort I (20\%): Complete function part1_histogram_compute() to accomplish the$ following: . Read the grayscale image called test.jpg 3. Plot the histogram. 4. Also, call Skimage and Numpy histogram functions to compute 256-bin histograms

with python

ort I (20\%): Complete function part1_histogram_compute() to accomplish the following: . Read the grayscale image called test.jpg 3. Plot the histogram. 4. Also, call Skimage and Numpy histogram functions to compute 256-bin histograms for the same image. Plot both histograms side by side with yours to show that they are identical. art II (30\%): Histogram equalization: e.,exposure.histogram, exposure.equalize_hist or any equivalent functions from any other library for this part. functions to compute the histograms. Part IV (40\%): Histogram matching: (a) (30\%) Grayscale: (b) (10\%) RGB: the third tutorial below. Show the RGB day, night and matched day images side by side

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