Histogram-Equalization

This project focuses on the implementation and evaluation of Histogram Equalization (HE) as a technique for enhancing image contrast. By developing algorithms for HE in popular programming languages and applying them to a diverse set of images, the project aims to showcase the versatility of this method. Visualizing original and equalized histograms, alongside quantitative metrics such as Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR), will provide a comprehensive understanding of the impact of histogram equalization on image quality. The project further investigates adaptability across different image types, ensuring a practical exploration of contrast enhancement techniques.