PSNR - Peak Signal-to-Noise Ratio

The PSNR (Peak Signal-to-Noise Ratio) method is a widely used approach for image quality assessment. It evaluates image quality by calculating the peak signal-to-noise ratio between the original image and the compressed/processed image. The PSNR method helps us understand the impact of compression algorithms on image quality and how different compression parameters affect the final output. Through PSNR evaluation, we can optimize compression parameters and select the most suitable algorithms to achieve better image quality. Implementation typically involves calculating the Mean Squared Error (MSE) between the original and processed images, then deriving PSNR using the formula: PSNR = 10·log₁₀(MAX²/MSE), where MAX represents the maximum possible pixel value (255 for 8-bit images). Key programming considerations include handling different image formats, ensuring proper data type conversion, and implementing efficient matrix operations for large images. Common functions used in implementation include image reading libraries (OpenCV, PIL) and mathematical operations for MSE calculation.