MATLAB Code Implementation for PSNR Calculation

This MATLAB code implements PSNR (Peak Signal-to-Noise Ratio) calculation to compare the peak signal values between two images. The implementation follows a structured computational approach: 1. The code begins by reading two input images and converting them to grayscale format using MATLAB's image processing functions like imread() and rgb2gray() for consistent pixel value comparison. 2. It then performs pixel-by-pixel comparison between the two images, calculating the difference matrix using element-wise subtraction operations between the image matrices. 3. The algorithm proceeds by squaring the difference values using element-wise power operations, then computes the Mean Squared Error (MSE) by taking the average of all squared differences across the entire image matrix. 4. Finally, the PSNR value is derived through logarithmic transformation of the MSE result, multiplied by a constant factor (typically 10 or 20) depending on the signal range, using the formula: PSNR = 10*log10(MAX^2/MSE) where MAX represents the maximum possible pixel value. This implementation serves as a quantitative tool for image quality assessment, enabling users to objectively evaluate similarity and differences between images through standardized signal-to-noise ratio metrics. The code incorporates proper matrix operations and error handling to ensure accurate comparison results for various image formats and sizes.