Curvature_Driven_Duffusion.rar_curvature_curvature driven_图像纹理信息

clear all; close all; clc; N=20000; D=1000; dt=0.4; nn=2; I=imread('lenna.bmp'); I=double(I); %% 构建以 (y0,x0) 为左顶点，高为 height，长为 width 的 mask y0=60;x0=100; height=20;width=10; y1=y0+height-1;x1=x0+width-1; I([y0:y1],[x0:x1])=zeros(height,width); figure(1);imshow(uint8(I)); %% 构建边缘，以 I0 作为修复区域的边界区域 k=3; tmp=I([y0-k:y1+k],[x0-k:x1+k]); I0=tmp; [ny,nx]=size(I0); %% 对 I0 进行曲率驱动扩散，并保持边界不动 for n=1:N I0x=0.5*(I0(:,[2:nx,nx])-I0(:,[1,1:nx-1])); I0y=0.5*(I0([2:ny,ny],:)-I0([1,1:ny-1],:)); gradient=sqrt(I0x.^2+I0y.^2+eps); I0xx=(I0(:,[2:nx,nx])-I0)-(I0-I0(:,[1,1:nx-1])); I0xy=0.25*((I0([2:ny,ny],[2:nx,nx])-I0([2:ny,ny],[1,1:nx-1]))-... (I0([1,1:ny-1],[2:nx,nx])-I0([1,1:ny-1],[1,1:nx-1]))); I0yy=(I0([2:ny,ny],:)-I0)-(I0-I0([1,1:ny-1],:)); kappa=(I0y.^2.*I0xx-2*I0x.*I0y.*I0xy+I0x.^2.*I0yy)./(gradient.^3); f=(abs(kappa)).^0.1; Diffusion=(f+f(:,[2:nx,nx]))./(gradient+gradient(:,[2:nx,nx])).*(I0(:,[2:nx,nx])-I0)-... (f+f(:,[1,1:nx-1]))./(gradient+gradient(:,[1,1:nx-1])).*(I0-I0(:,[1,1:nx-1]))+... (f+f([2:ny,ny],:))./(gradient+gradient([2:ny,ny],:)).*(I0([2:ny,ny],:)-I0)-... (f+f([1,1:ny-1],:))./(gradient+gradient([1,1:ny-1],:)).*(I0-I0([1,1:ny-1],:)); I0=I0+dt*Diffusion; I0([1:k,height+k+1:height+2*k],[1:k,width+k+1:width+2*k])... =tmp([1:k,height+k+1:height+2*k],[1:k,width+k+1:width+2*k]); % 修复区域外面保持不动 %% 输出图像 if mod(n,D)==0 I([y0:y1],[x0:x1])=I0([1:height],[1:width]); figure(nn); imshow(uint8(I)); nn=nn+1; end n % 输出 n，而于 matlab 窗口看运行截止时间 end