Image Peak Signal-to-Noise Ratio (PSNR) Calculation with MATLAB Implementation

This MATLAB source code calculates the Peak Signal-to-Noise Ratio (PSNR) for images and includes functionality to convert relative paths to absolute paths. PSNR calculation is a fundamental metric for evaluating image quality by comparing the difference between original and processed images. The algorithm works by computing the mean squared error (MSE) between the two images and then deriving PSNR using the formula: PSNR = 20·log10(MAX_I/√MSE), where MAX_I represents the maximum possible pixel value (typically 255 for 8-bit images). Higher PSNR values indicate better image quality with less distortion. The MATLAB implementation includes key functions such as imread() for image loading, im2double() for pixel value normalization, and mean2() for MSE calculation. The path conversion module utilizes MATLAB's fullfile() and fileparts() functions to handle relative path resolution, ensuring robust file access regardless of the current working directory. This program enables efficient PSNR calculation for image quality assessment and provides reliable path management for file operations. Users can easily compute PSNR values and ensure proper file path handling for seamless program execution across different directory structures. The code implementation follows MATLAB best practices with clear variable naming and error handling mechanisms. For optimal results, ensure input images have identical dimensions and compatible data types before PSNR calculation. These modifications and enhancements provide comprehensive understanding of the program's functionality. Please feel free to ask if you have any questions about the implementation details or usage scenarios.