Image Processing Applications for PSNR and MSE Metrics

This collection features several MATLAB-implemented image processing utilities centered on PSNR (Peak Signal-to-Noise Ratio) and MSE (Mean Squared Error) metrics, intended to support research in image quality assessment and compression techniques. The implementations include core algorithms for calculating pixel-wise differences between original and processed images, with MSE quantifying average squared error per pixel and PSNR deriving logarithmic quality measurements from MSE results. Through systematic computation of these metrics, users can quantitatively evaluate the performance and effectiveness of various image processing algorithms. These utilities employ matrix operations for efficient error computation and include normalization handling for different image formats. The code structure facilitates easy integration with existing image processing pipelines, helping researchers better understand and apply fundamental image quality assessment techniques in practical scenarios.