Needed Full code for Color to grayscale and Wiener Algorithm for deblurring and differences between Original and Final Deblurred

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Kartikeya
Kartikeya 2023-11-9
回答： Drishti 2024-9-24
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Needed Full code for Color to grayscale and Wiener Algorithm for deblurring and differences between Original and Final Deblurred
% Load the original image
Ioriginal = imread('greyface1.jpg');
imshow(Ioriginal);
title('Original Image');
% Define the motion blur point spread function (PSF)
PSF = fspecial('motion', 21, 11);
% Convert the original image to double
Ioriginal = im2double(Ioriginal);
% Apply motion blur to the original image
blurred = imfilter(Ioriginal, PSF, 'conv', 'circular');
imshow(blurred);
title('Blurred Image');
% Restore the blurred image without noise
wnr1 = deconvwnr(blurred, PSF);
% Calculate the absolute differences between the original and restored images
err = imabsdiff(Ioriginal, wnr1);
% Display the restored image
imshow(wnr1);
title('Restored Blurred Image');
% Create a histogram of the absolute differences
figure;
histogram(err);
title('Histogram of Absolute Differences');
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Drishti
Drishti 2024-9-24
Hi Kartikeya,
To convert the RGB image to Grayscale, you can utilize the ‘rgb2gray’ function available in MATLAB.
Refer to the implementation below to convert the RGB image to Grayscale.
% Convert RGB image to grayscale
imgGray = rgb2gray(imgRGB);
For deblurring the image using Wiener Algorithm, you can utilize ‘deconvwnr’ function which deconvolves the image using Wiener filter algorithm.
Following example clarifies the implementation of ‘deconvwnr’ function:
% Deblur the image using Wiener filter
estimatedNSR = 0.01; % Estimated noise-to-signal power ratio
imgDeblurred = deconvwnr(imgBlurred, h, estimatedNSR);
Furthermore, to check the pixel-by-pixel difference in the original image and final output image, you can leverage the ‘imabsdiff’ function and visualize it using a histogram.
You can refer to the below given code snippet:
% Calculate pixel-by-pixel difference
difference = imabsdiff(imgGray, imgDeblurred);
% Plot histogram of differences
figure;
histogram(difference(:), 'BinWidth', 1);
title('Histogram of Pixel Differences');
xlabel('Difference Value');
ylabel('Frequency');
For more information, you can refer to the following MathWorks Documentation:
I hope this resolves the query.

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