Source Code for Two Histogram Equalization Methods

This article presents MATLAB source code implementations for two distinct histogram equalization methods. Histogram equalization is a fundamental image processing technique designed to enhance image contrast by redistributing pixel intensity values across a wider dynamic range. The algorithm works by calculating the cumulative distribution function of the original histogram and mapping pixel values to achieve a more uniform distribution, thereby making image details more prominent and improving overall visual quality. The provided source codes implement two variations of histogram equalization: 1. Standard global histogram equalization that processes the entire image 2. An enhanced method with additional parameters for customized contrast adjustment Key implementation features include: - Efficient histogram computation using MATLAB's built-in functions - Cumulative distribution calculation and mapping operations - Optional parameters for controlling enhancement intensity - Compatibility with various image formats (RGB, grayscale) These ready-to-use code implementations can be directly integrated into your image processing projects to improve image quality and enhance visual clarity. The codes include comprehensive comments explaining each processing step and parameter usage. Feel free to download and experiment with these implementations - we believe they will provide valuable contributions to your image enhancement workflows.