谁有用MATLAB编写的关于小波变换数字图像数字边缘提取的程序?
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发布时间:2024-10-23 18:37
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时间:2024-11-01 20:44
基于小波变换的多尺度图像边缘检测matlab源代码,适用于Matlab7.0环境。
在Matlab环境下运行此代码前,请确保已加载图像数据,具体操作如下:
clear all;
load wbarb;
I = ind2gray(X,map);
imshow(I);
进行图像调整以优化显示效果:
I1 = imadjust(I,stretchlim(I),[0,1]);
figure;
imshow(I1);
定义图像尺寸与相关系数向量。
[N,M] = size(I);
h = [0.125,0.375,0.375,0.125];
g = [0.5,-0.5];
delta = [1,0,0];
J = 3;
a(1:N,1:M,1,1:J-1) = 0;
dx(1:N,1:M,1,1:J-1) = 0;
dy(1:N,1:M,1,1:J-1) = 0;
d(1:N,1:M,1,1:J-1) = 0;
进行第一轮边缘检测。
a(:,:,1,1) = conv2(h,h,I,'same');
dx(:,:,1,1) = conv2(delta,g,I,'same');
dy(:,:,1,1) = conv2(g,delta,I,'same');
x = dx(:,:,1,1);
y = dy(:,:,1,1);
d(:,:,1,1) = sqrt(x^2+y^2);
I1 = imadjust(d(:,:,1,1),stretchlim(d(:,:,1,1)),[0 1]);
figure;
imshow(I1);
定义循环变量和相关系数调整参数,进行多尺度边缘检测。
lh = length(h);
lg = length(g);
for j = 1:J-1
lhj = 2^j*(lh-1)+1;
lgj = 2^j*(lg-1)+1;
hj(1:lhj)=0;
gj(1:lgj)=0;
for n = 1:lh
hj(2^j*(n-1)+1)=h(n);
end
for n = 1:lg
gj(2^j*(n-1)+1)=g(n);
end
a(:,:,1,j) = conv2(hj,hj,a(:,:,1,j),'same') ;
dx(:,:,1,j) = conv2(delta,gj,a(:,:,1,j),'same');
dy(:,:,1,j) = conv2(gj,delta,a(:,:,1,j),'same');
x = dx(:,:,1,j);
y = dy(:,:,1,j);
dj(:,:,1,j) = sqrt(x^2+y^2);
I1 = imadjust(dj(:,:,1,j),stretchlim(dj(:,:,1,j)),[0 1]);
figure;
imshow(I1);
end
通过上述MATLAB代码,实现了基于小波变换的多尺度图像边缘检测。根据具体需求,调整代码参数,可以实现不同尺度下的边缘提取功能。