General information

Some basic image processing examples with MATLAB.

Content

• histeq()
• imadjust()
• The Negative of an Image
• Binary Image

histeq()

Enhance contrast using histogram equalization. Input: grayscale image. Output: adjusted image.

imadjust()

Adjust image intensity values.

Negative of an Image

Get the negative of an image

Finding the negative of an image by changing the intensity levels of the pixels present in the image.

Get the negative of an image using loops

Checks if image is either grayscale or RGB, and depends on statement choose loop. Works good on grayscale images but slow on RGB.

Grayscale:

if size(image,3) == 1
    [n,m] = size(image);
    for i = 1:n
        for j = 1:m
            image_negative(i,j) = 255 - image(i,j);
        end
    end
    subplot(1,2,2);
    imshow(image_negative), title('Negative');

RGB:

elseif size(image,3) == 3
    [n,m,p] = size(image);
    for i = 1:n
        for j = 1:m
            for k = 1:p
                image_negative(i,j,k) = 255 - image(i,j,k);
            end
        end
    end
    subplot(1,2,2);
    imshow(image_negative), title('Negative');
end

Complement image

We can also get the negative of an image using MATLAB's built-in function imcomplement(). It subtracts the pixel value from the maximum pixel value of the image class.

Binary Image

Converting grayscale image to binary (black and white) image.

Converting RGB image to binary.