Easy PSNR and SSIM calculation? [closed]

1. How is PSNR calculated?
2. Which is better PSNR or SSIM?
3. What is a good PSNR value in image processing?
4. How to calculate PSNR and SSIM Python?

How is PSNR calculated?

Peak signal-to-noise ratio (PSNR) is the ratio between the maximum possible power of an image and the power of corrupting noise that affects the quality of its representation. To estimate the PSNR of an image, it is necessary to compare that image to an ideal clean image with the maximum possible power.

Which is better PSNR or SSIM?

Based on the results of tests on this research SSIM has a better sensitivity to detect distortions that occur due to embedding messages on steganographic color images when compared with PSNR, this is due to the way SSIM works that are designed based on the human visual system.

What is a good PSNR value in image processing?

Typical values for the PSNR in lossy image and video compression are between 30 and 50 dB, provided the bit depth is 8 bits, where higher is better. The processing quality of 12-bit images is considered high when the PSNR value is 60 dB or higher. For 16-bit data typical values for the PSNR are between 60 and 80 dB.

How to calculate PSNR and SSIM Python?

filter2D(img1 * img2, -1, window)[5:-5, 5:-5] - mu1_mu2 ssim_map = ((2 * mu1_mu2 + C1) * (2 * sigma12 + C2)) / ((mu1_sq + mu2_sq + C1) * (sigma1_sq + sigma2_sq + C2)) return ssim_map. mean() def calculate_ssim(img1, img2): '''calculate SSIM the same outputs as MATLAB's img1, img2: [0, 255] ''' if not img1.