MATLAB Code Implementation for Image Preprocessing Algorithms

Implementation of image preprocessing algorithms using MATLAB. The algorithms cover median filtering, morphological filtering, binarization processing, and image background correction. During image preprocessing, median filtering can be implemented using the medfilt2() function to eliminate image noise while preserving edge information. Morphological filtering operations like erosion and dilation can be performed using imerode() and imdilate() functions to smooth images and enhance edge features. Binarization processing can be achieved through thresholding techniques using imbinarize() or graythresh() functions to convert images into binary representations with black and white pixels. Image background correction algorithms utilize histogram equalization (histeq()) or contrast adjustment (imadjust()) functions to optimize image brightness and contrast levels. These preprocessing techniques are fundamental in image processing workflows and significantly improve the accuracy and effectiveness of subsequent image recognition and analysis tasks through proper noise reduction and feature enhancement.