MATLAB Implementation of Histogram Equalization for Image Enhancement

This program implements the histogram equalization function for digital images. Histogram equalization is a fundamental image processing technique that enhances image quality by redistributing pixel intensity values across the histogram. The algorithm works by calculating the cumulative distribution function of the original histogram and mapping pixel values to create a more uniform distribution. Key implementation steps include: computing the image histogram, calculating the cumulative distribution function, and applying the transformation mapping to all pixels. This process effectively improves image contrast, making details more visible and colors more vibrant. The program provides significant utility in various image processing applications such as medical imaging, photography enhancement, and computer vision tasks. By utilizing this implementation, users can efficiently enhance image quality, revealing subtle details and improving overall visual appearance. The code demonstrates essential MATLAB functions like histcounts for histogram calculation and array operations for efficient pixel value mapping. This implementation serves as an indispensable tool in the image processing domain, offering both educational value and practical application capabilities for professionals and researchers working with digital image analysis.