abc.zip_ABC_ABC image_ABC 图像处理_图像压缩

% ********** Do not distribute this file *********** % This Matlab program implements the level set method in Li et al's paper % "Level Set Evolution Without Re-initialization: A New Variational Formulation" % in Proceedings of CVPR'05, vol. 1, pp. 430-436. % Copyright (c) 2004--2007 by Chunming Li % Author: Chunming Li % Revision by Chunming Li 4/25/2006 % e-mail: li_chunming@hotmail.com % http://vuiis.vanderbilt.edu/~licm/ % clear all; % close all; % % Img = imread('twocells.bmp'); % The same cell image in the paper is used here % % Img = imread('D2.bmp'); % Img = imread('test.bmp'); % Img=double(Img(:,:,1)); % Img = Img + 127; % sigma=1; % scale parameter in Gaussian kernel. % G=fspecial('gaussian',15,sigma); % Img_smooth=conv2(Img,G,'same'); % smooth image by Gaussiin convolution % [Ix,Iy]=gradient(Img_smooth); % imshow(uint8(Img_smooth)); % figure; % f=Ix.^2+Iy.^2; fp = fopen('nominal1.txt', 'r'); m = fscanf(fp,'%d,%d'); fscanf(fp,';'); n = fscanf(fp,'%f,'); rm1 = reshape(n,m(2),m(1)); rm = rm1; rm1 = rm'; rm1 = rm1(:,m(2):-1:1); Img = rm1'; fclose(fp); [X Y] = meshgrid(0:size(Img,1)-1,0:size(Img,2)-1); [K,H,P1,P2] = surfature(X,Y,Img); Img = H; % Ix = diff(Img_smooth,2,1); % Iy = diff(Img_smooth,2,2); % Ix=Ix(:,2:end-1); % Iy=Iy(2:end-1,:); % f=(Ix.^2+Iy.^2)*8; % % Img_smooth=Img_smooth(2:end-1,2:end-1); % Img=Img(2:end-1,2:end-1); % g = max(max(f))-f; % Ix = diff(Img_smooth,3,1); % Iy = diff(Img_smooth,3,2); % Ix=Ix(:,2:end-2); % Iy=Iy(2:end-2,:); % f=(Ix.^2+Iy.^2)*8; % Img=Img(2:end-2,2:end-2); [Ix,Iy]=gradient(H); f=(Ix.^2+Iy.^2); ff = mat2gray(f); imshow(ff); g=1./(1+f); % edge indicator function. % g=1./(1+H); gg = mat2gray(g); imshow(gg); lambda=150; % coefficient of the weighted length term L(\phi) mu=0.04; % coefficient of the internal (penalizing) energy term P(\phi) alf=10; % coefficient of the weighted area term A(\phi) epsilon=1.5; % the papramater in the definition of smooth Dirac function timestep=5; % time step % define initial level set function (LSF) as -c, 0, c at points outside, on % the boundary, and inside of a region R, respectively. [nrow, ncol]=size(Img); c=10; initialLSF=c*ones(nrow,ncol); d=8; initialLSF(d+1:end-d, d+1:end-d)=0; % zero level set on the boundary of R initialLSF(d+2:end-d-1, d+2: end-d-1)=-c; % negative constant inside of R u=initialLSF; figure;imagesc(Img);colormap(gray);hold on; [c,h] = contour(u,[0 0],'r','LineWidth',2); % pause(3); title('Initial contour'); % start level set evolution for n=1:880 u=EVOLUTION_PLSE(u, g ,lambda, mu, alf, epsilon, timestep, 1); pause(0.02); if mod(n,20)==0 imagesc(Img);colormap(gray);hold on; axis equal; axis off; [c,h] = contour(u,[0 0],'g','LineWidth',3); iterNum=[num2str(n), ' iterations']; title(iterNum); hold off; end end imagesc(Img);colormap(gray);hold on; [c,h] = contour(u,[0 0],'g','LineWidth',4); totalIterNum=[num2str(n), ' iterations']; title(['Final contour, ', totalIterNum]);