MATLAB Code for Calculating Image Peak Signal-to-Noise Ratio (PSNR)
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Resource Overview
MATLAB implementation for computing Peak Signal-to-Noise Ratio (PSNR) of images with detailed code explanation and algorithm breakdown
Detailed Documentation
This MATLAB implementation calculates the Peak Signal-to-Noise Ratio (PSNR), a fundamental quality assessment metric in image processing that quantifies the ratio between the maximum possible signal power and the corrupting noise power. The algorithm works by computing the Mean Squared Error (MSE) between the original image and the processed image, then deriving PSNR using logarithmic scaling. The key implementation involves handling different image data types (uint8, double) and dynamic range considerations. The code typically uses matrix operations for efficient MSE calculation and includes proper error handling for dimension matching. For optimal performance, the implementation normalizes pixel values and handles edge cases like identical images (which would yield infinite PSNR). The MATLAB environment provides built-in functions for image reading and mathematical operations that streamline the PSNR computation process.
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