图像信噪比_

function PSNR(A,B) % PURPOSE: To find the PSNR (peak signal-to-noise ratio) between two % intensity images A and B, each having values in the interval % [0,1]. The answer is in decibels (dB). % % SYNOPSIS: PSNR(A,B) % % DESCRIPTION: The following is quoted from "Fractal Image Compression", % by Yuval Fisher et al.,(Springer Verlag, 1995), % section 2.4, "Pixelized Data". % % "...PSNR is used to measure the difference between two % images. It is defined as % % PSNR = 20 * log10(b/rms) % % where b is the largest possible value of the signal % (typically 255 or 1), and rms is the root mean square % difference between two images. The PSNR is given in % decibel units (dB), which measure the ratio of the peak % signal and the difference between two images. An increase % of 20 dB corresponds to a ten-fold decrease in the rms % difference between two images. % % There are many versions of signal-to-noise ratios, but % the PSNR is very common in image processing, probably % because it gives better-sounding numbers than other % measures." % % EXAMPLE 1: load clown % A = ind2gray(X,map); % Convert to an intensity image in [0,1]. % B = 0.95 * A; % Make B close to, but different from, A. % PSNR(A,B) % ---> "PSNR = +33.49 dB" % % EXAMPLE 2: A = rand(256); % A is a random 256 X 256 matrix in [0,1]. % B = 0.9 * A; % Make B close to, but different from, A. % PSNR(A,B) % ---> "PSNR = +24.76 dB (approx)" if A == B error('Images are identical: PSNR has infinite value') end max2_A = max(max(A)); max2_B = max(max(B)); min2_A = min(min(A)); min2_B = min(min(B)); if max2_A > 1 | max2_B > 1 | min2_A < 0 | min2_B < 0 error('input matrices must have values in the interval [0,1]') end error = A - B; decibels = 20*log10(1/(sqrt(mean(mean(error.^2))))); disp(sprintf('PSNR = +%5.2f dB',decibels))