Calculating PSNR for Two Color Images

In this article, we present a robust image processing algorithm designed to compute the Peak Signal-to-Noise Ratio (PSNR) between two color images for evaluating image processing effectiveness. The algorithm processes RGB channels independently by first converting images to double precision, calculating Mean Squared Error (MSE) for each channel using element-wise differences, and then combining results for final PSNR computation. Implementation typically involves matrix operations for efficient pixel-wise comparison and logarithmic conversion for dB scale output. This method finds applications in various domains including image compression, denoising, and enhancement techniques. By employing this algorithm, researchers can quantitatively assess image processing method performance and conduct more accurate comparative evaluations between different algorithms. Consequently, this tool serves as a valuable asset in the image processing field, facilitating better understanding and optimization of image processing methodologies through standardized quality metrics.