Contrast Enhancement, Histogram Equalization, and Filtering Algorithms

This repository provides MATLAB source codes for fundamental image processing operations, including contrast enhancement, histogram equalization, and filtering algorithms. Each implementation contains detailed comments and follows MATLAB best practices for image manipulation. The contrast enhancement module utilizes intensity transformation functions to expand the dynamic range of pixel values, making image details more prominent through techniques like histogram stretching or gamma correction. Histogram equalization implementations feature probability distribution calculations and cumulative distribution functions to redistribute intensity values, creating more balanced images with improved brightness and contrast characteristics. The filtering section includes spatial domain implementations using convolution operations with various kernel types (mean, Gaussian, median) for effective noise reduction and image smoothing. These codes demonstrate practical applications of digital image processing theory, supporting both grayscale and color image processing through matrix operations and built-in MATLAB functions like imadjust, histeq, and imfilter. Whether you're a professional in computer vision or a student learning image processing fundamentals, these well-documented implementations will help you understand algorithm mechanics and apply them to improve image clarity, enhance structural hierarchy, and reduce noise artifacts. We hope you enjoy exploring these practical examples and gain valuable insights into image processing techniques.