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Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.

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📚 Computational Methods with MATLAB (2023)

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📚 Machine and Deep Learning Using MATLAB (2023)

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📚 Mastering MATLAB (2024)

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📚 MATLAB for Machine Learning (2024)

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📚 MATLAB Machine Learning Recipes (2024)

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📚 MATLAB for Machine Learning (2024)

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📚 Digital Image Denoising in MATLAB (2024)

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📚 MATLAB (2024)

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Top 30 MATLAB Image Processing Functions

#MATLAB #ImageProcessing #Basics

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Top 30 MATLAB Image Processing Functions

#MATLAB #ImageProcessing #Basics

#1. imread()
Reads an image from a file into a matrix.

img = imread('peppers.png');
disp('Image "peppers.png" loaded into variable "img".');

Image "peppers.png" loaded into variable "img".


#2. imshow()
Displays an image in a figure window.

img = imread('peppers.png');
imshow(img);
title('Peppers Image');

Output: A new figure window opens, displaying the 'peppers.png' image with the title "Peppers Image".


#3. imwrite()
Writes an image matrix to a file.

img = imread('cameraman.tif');
imwrite(img, 'my_cameraman.jpg');
disp('Image saved as my_cameraman.jpg');

Image saved as my_cameraman.jpg


#4. size()
Returns the dimensions of the image matrix (rows, columns, color channels).

rgb_img = imread('peppers.png');
gray_img = imread('cameraman.tif');
size_rgb = size(rgb_img);
size_gray = size(gray_img);
disp(['Size of RGB image: ', num2str(size_rgb)]);
disp(['Size of grayscale image: ', num2str(size_gray)]);

Size of RGB image: 384   512     3
Size of grayscale image: 256 256


#5. rgb2gray()
Converts an RGB color image to a grayscale intensity image.

rgb_img = imread('peppers.png');
gray_img = rgb2gray(rgb_img);
imshow(gray_img);
title('Grayscale Peppers');

Output: A figure window displays the grayscale version of the peppers image.

---
#MATLAB #ImageProcessing #Conversion #Transformation

#6. im2double()
Converts an image to double-precision format, scaling data to the range [0, 1].

img_uint8 = imread('cameraman.tif');
img_double = im2double(img_uint8);
disp(['Max value of original image: ', num2str(max(img_uint8(:)))]);
disp(['Max value of double image: ', num2str(max(img_double(:)))]);

Max value of original image: 253
Max value of double image: 0.99216


#7. imresize()
Resizes an image to a specified size.

img = imread('cameraman.tif');
resized_img = imresize(img, 0.5); % Resize to 50% of original size
imshow(resized_img);
title('Resized Cameraman');

Output: A figure window displays the cameraman image at half its original size.


#8. imrotate()
Rotates an image by a specified angle.

img = imread('cameraman.tif');
rotated_img = imrotate(img, 30, 'bilinear', 'crop');
imshow(rotated_img);
title('Rotated 30 Degrees');

Output: A figure window displays the cameraman image rotated by 30 degrees, cropped to the original size.


#9. imcrop()
Crops an image to a specified rectangle.

img = imread('peppers.png');
% [xmin ymin width height]
cropped_img = imcrop(img, [100 80 250 200]);
imshow(cropped_img);
title('Cropped Image');

Output: A figure window displays only the rectangular section specified from the peppers image.


#10. rgb2hsv()
Converts an RGB image to the Hue-Saturation-Value (HSV) color space.

rgb_img = imread('peppers.png');
hsv_img = rgb2hsv(rgb_img);
hue_channel = hsv_img(:,:,1); % Extract the Hue channel
imshow(hue_channel);
title('Hue Channel of Peppers Image');

Output: A figure window displays the Hue channel of the peppers image as a grayscale image.

---
#MATLAB #ImageProcessing #Enhancement

#11. imhist()
Displays the histogram of an image, showing the distribution of pixel intensity values.
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