HVS의 이미지 싱크로율 지침으로 WPSNR 계산

   MATLAB                。     PSNR  ,   HVS(human visual sytem)   。













function f = WPSNR(A,B,varargin) % This function computes WPSNR (weighted peak signal-to-noise ratio) between % two images. The answer is in decibels (dB). % % Using contrast sensitivity function (CSF) to weight spatial frequency % of error image. % % Using: WPSNR(A,B) % % Written by Ruizhen Liu, http://www.assuredigit.com 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 e = A - B; if nargin<3 fc = csf; % filter coefficients of CSF else fc = varargin{1}; end ew = filter2(fc, e); % filtering error with CSF decibels = 20*log10(1/(sqrt(mean(mean(ew.^2))))); % disp(sprintf('WPSNR = +%5.2f dB',decibels)) f=decibels; %============= function fc = csf() %============= % Program to compute CSF % Compute contrast sensitivity function of HVS % % Output: fc --- filter coefficients of CSF % % Reference: % Makoto Miyahara % "Objective Picture Quality Scale (PQS) for Image Coding" % IEEE Trans. on Comm., Vol 46, No.9, 1998. % % Written by Ruizhen Liu, http://www.assuredigit.com % compute frequency response matrix Fmat = csfmat; % Plot frequency response %mesh(Fmat); pause % compute 2-D filter coefficient using FSAMP2 fc = fsamp2(Fmat); %mesh(fc) %======================== function Sa = csffun(u,v) %======================== % Contrast Sensitivity Function in spatial frequency % This file compute the spatial frequency weighting of errors % % Reference: % Makoto Miyahara % "Objective Picture Quality Scale (PQS) for Image Coding" % IEEE Trans. on Comm., Vol 46, No.9, 1998. % % Input : u --- horizontal spatial frequencies % v --- vertical spatial frequencies % % Output: frequency response % % Written by Ruizhen Liu, http://www.assuredigit.com % Compute Sa -- spatial frequency response %syms S w sigma f u v sigma = 2; f = sqrt(u.*u+v.*v); w = 2*pi*f/60; Sw = 1.5*exp(-sigma^2*w^2/2)-exp(-2*sigma^2*w^2/2); % Modification in High frequency sita = atan(v./(u+eps)); bita = 8; f0 = 11.13; w0 = 2*pi*f0/60; Ow = ( 1 + exp(bita*(w-w0)) * (cos(2*sita))^4) / (1+exp(bita*(w-w0))); % Compute final response Sa = Sw * Ow; %=================== function Fmat = csfmat() %=================== % Compute CSF frequency response matrix % Calling function csf.m % frequency range % the rang of frequency seems to be: % w = pi = (2*pi*f)/60 % f = 60*w / (2*pi), about 21.2 % min_f = -20; max_f = 20; step_f = 1; u = min_f:step_f:max_f; v = min_f:step_f:max_f; n = length(u); Z = zeros(n); for i=1:n for j=1:n Z(i,j)=csffun(u(i),v(j)); % calling function csffun end end Fmat = Z;

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