gray_img = imread('pout.tif');
imhist(gray_img);
title('Histogram of a Low-Contrast Image');

Output: A figure window with a bar chart showing the intensity distribution of the 'pout.tif' image.

#12. histeq()
Enhances contrast using histogram equalization.

low_contrast_img = imread('pout.tif');
high_contrast_img = histeq(low_contrast_img);
imshow(high_contrast_img);
title('Histogram Equalized Image');

Output: A figure window displays a higher contrast version of the 'pout.tif' image.

#13. imadjust()
Adjusts image intensity values or colormap by mapping intensity values to new values.

img = imread('cameraman.tif');
adjusted_img = imadjust(img, [0.3 0.7], []);
imshow(adjusted_img);
title('Intensity Adjusted Image');

Output: A figure window showing a high-contrast version of the cameraman image, where intensities between 0.3 and 0.7 are stretched to the full [0, 1] range.

#14. imtranslate()
Translates (shifts) an image horizontally and vertically.

img = imread('cameraman.tif');
translated_img = imtranslate(img, [25, 15]); % Shift 25 pixels right, 15 pixels down
imshow(translated_img);
title('Translated Image');

Output: A figure window shows the cameraman image shifted to the right and down.

#15. imsharpen()
Sharpens an image using the unsharp masking method.

img = imread('peppers.png');
sharpened_img = imsharpen(img);
imshow(sharpened_img);
title('Sharpened Image');

Output: A figure window displays a crisper, more detailed version of the peppers image.

---
#MATLAB #ImageProcessing #Filtering #Noise

#16. imnoise()
Adds a specified type of noise to an image.

img = imread('cameraman.tif');
noisy_img = imnoise(img, 'salt & pepper', 0.02);
imshow(noisy_img);
title('Image with Salt & Pepper Noise');

Output: A figure window displays the cameraman image with random white and black pixels (noise).

#17. fspecial()
Creates a predefined 2-D filter kernel (e.g., for averaging, Gaussian blur, Laplacian).

h = fspecial('motion', 20, 45); % Create a motion blur filter
disp('Generated a 2D motion filter kernel.');
disp(h);

Generated a 2D motion filter kernel.
(Output is a matrix representing the filter kernel)

#18. imfilter()
Filters a multidimensional image with a specified filter kernel.

img = imread('cameraman.tif');
h = fspecial('motion', 20, 45);
motion_blur_img = imfilter(img, h, 'replicate');
imshow(motion_blur_img);
title('Motion Blurred Image');

Output: A figure window shows the cameraman image with a motion blur effect applied at a 45-degree angle.

#19. medfilt2()
Performs 2-D median filtering, which is excellent for removing 'salt & pepper' noise.

noisy_img = imnoise(imread('cameraman.tif'), 'salt & pepper', 0.02);
denoised_img = medfilt2(noisy_img);
imshow(denoised_img);
title('Denoised with Median Filter');

Output: A figure window shows the noisy image significantly cleaned up, with most salt & pepper noise removed.

#20. edge()
Finds edges in an intensity image using various algorithms (e.g., Sobel, Canny).