matlab-(含教程)基于LS最小二乘法的纹理图片深度信息提取算法matlab仿真

function Depth = estimate_depth(I1,I2,Hp,visualize) On = 1; Off = 0; if nargin<4 % visualize partial results while estimating depth map (slow) visualize = Off; elseif (visualize ~= On) & (visualize ~= Off) % visualize partial results while estimating depth map (slow) visualize = Off; end if nargin<3 fid=fopen('Operators.mat','r'); fclose(fid); if fid==-1 error('No operators found. Run generate_operators first.') end load Operators end if nargin<2 error('Too few arguments!'); end numlevels = size(Hp,3); ni = sqrt(size(Hp,1)/2); if ni~=floor(ni) error('Orthogonal operators have incorrect size!'); end dI1 = del2(I1); dI2 = del2(I2); [mI,nI] = size(I1); % compute depth level fprintf('Computing depth levels\n'); fprintf('%i Iterations',numlevels) Cost = zeros(mI*nI,numlevels); C = zeros(mI*nI,size(Hp,1)); for i = 1:numlevels for k=1:size(Hp,1) P1 = reshape(Hp(k,ni*ni:-1:1,i,1),ni,ni); P2 = reshape(Hp(k,ni*ni+[ni*ni:-1:1],i,1),ni,ni); C(:,k) = reshape(conv2(dI1,P1,'same')+... conv2(dI2,P2,'same'),mI*nI,1); end Flt = C*Hp(:,:,i); Cost(:,i) = sum(Flt.^2,2); if visualize [dummy,Depth] = min(Cost(:,1:i),[],2); Depth = reshape(Depth,mI,nI); % visualize result figure(1) set(gcf,'name',sprintf('Iteration %3i out of %3i',i,numlevels)); subplot(221) image(I1) axis equal axis off set(gca,'XTick',[],'YTick',[]); set(gca,'Box','off'); colormap gray(256) title('Input #1') drawnow; subplot(222) image(I2) axis equal axis off set(gca,'XTick',[],'YTick',[]); set(gca,'Box','off'); colormap gray(256) title('Input #2') drawnow; step = ceil(min([size(Depth,1) ... size(Depth,2)])/50); pix2mm = 1/2; [X,Y] = meshgrid(pix2mm*[1:step:size(Depth,2)],... pix2mm*[1:step:size(Depth,1)]); axisZ = [0 numlevels]; subplot(223) h = surf(X,-Depth(1:step:end,1:step:end),-Y,Depth(1:step:end,1:step:end)); shading interp hold off axis([0 nI -axisZ(2) -axisZ(1) -mI 0]) set(gca,'XTick',[],'YTick',[],'ZTick',[]); colormap gray(256) title('Estimated Depth Map') view([-1 -2 1]); axis equal axis off set(h,'EdgeColor','r'); drawnow; subplot(224) imagesc(Depth); colormap gray(256) %axis off axis equal set(gca,'XTick',[],'YTick',[]); set(gca,'Box','off'); title('Estimated Depth Map') drawnow; end end % find minimum of the cost functional [dummy,Depth] = min(Cost,[],2); Depth = reshape(Depth,mI,nI); fprintf('\ndone.\n'); return