PSNRään

PSNR is a metric used to measure the quality of reconstruction of a lossy compression code, such as that of digital images or video. It is defined as the ratio between the maximum possible power of a signal and the power of corrupting noise that affects the fidelity of its representation. PSNR is most commonly used to measure the quality of reconstruction of lossy compressed images or videos. The higher the PSNR value, the better the quality of the reconstructed image or video.

PSNR is calculated using the mean squared error (MSE) between the original and reconstructed images. The MSE is the average of the squared differences between the pixels of the original and reconstructed images. The PSNR is then calculated as 20 * log10(MAXI / sqrt(MSE)), where MAXI is the maximum possible pixel value. For an 8-bit grayscale image, MAXI is 255.

PSNR is a widely used metric, but it has some limitations. For example, it does not always correlate well with human perception of image quality. In some cases, an image with a lower PSNR may appear to be of higher quality to a human observer. This is because PSNR does not take into account the perceptual characteristics of the human visual system. Despite its limitations, PSNR remains a useful metric for evaluating the quality of image and video compression.