%下面涉及到的主要还是公式编程,具体的算法和你的资料一样,我就不详细介绍算法了,如有对函数不理解的再联系我
Gray = imread('C:\Users\Administrator\Desktop\各种特征\GLCM\2034.pgm');
[M,N,O] = size(Gray);
%下面2行用于对待大图片,强制截取其一部分,减少运算量,由于是基于统计,所以对结果影响不大
%M = 256; %此2行与19、20行相关,详见19、20行
%N = 256;
%--------------------------------------------------------------------------
%1.将各颜色分量转化为灰度,如果图像是灰度图像,就注释掉此段
% 如果未注释此行,运行会出现报错“Index exceeds matrix dimensions.”
%--------------------------------------------------------------------------
% Gray = double(0.3*Gray(:,:,1)+0.59*Gray(:,:,2)+0.11*Gray(:,:,3));
%--------------------------------------------------------------------------
%2.为了减少计算量,对原始图像灰度级压缩,将Gray量化成16级
%--------------------------------------------------------------------------
for i = 1:M
for j = 1:N
%for n=1:floor(M+N/2)/16 %如果5、6行被注释,则使用此行。floor函数为向负无穷大方向近似,即近似为等于或小于自己的整数
for n = 1:256/16 %如果5、6行未注释,则使用此行(其实5、6行注释与否使用上行结果都一样,因为M+N/2==256)
if (n-1)*16<=Gray(i,j)&Gray(i,j)<=(n-1)*16+15
Gray(i,j) = n-1;
end
end
end
end
%--------------------------------------------------------------------------
%3.计算四个共生矩阵P,取距离为1,角度分别为0,45,90,135
%--------------------------------------------------------------------------
P = zeros(16,16,4);
for m = 1:16
for n = 1:16
for i = 1:M
for j = 1:N
if j<N&Gray(i,j)==m-1&Gray(i,j+1)==n-1
P(m,n,1) = P(m,n,1)+1;
P(n,m,1) = P(m,n,1);
end
if i>1&j<N&Gray(i,j)==m-1&Gray(i-1,j+1)==n-1
P(m,n,2) = P(m,n,2)+1;
P(n,m,2) = P(m,n,2);
end
if i<M&Gray(i,j)==m-1&Gray(i+1,j)==n-1
P(m,n,3) = P(m,n,3)+1;
P(n,m,3) = P(m,n,3);
end
if i<M&j<N&Gray(i,j)==m-1&Gray(i+1,j+1)==n-1
P(m,n,4) = P(m,n,4)+1;
P(n,m,4) = P(m,n,4);
end
end
end
if m==n
P(m,n,:) = P(m,n,:)*2;
end
end
end
%%---------------------------------------------------------
% 对共生矩阵归一化
%%---------------------------------------------------------
for n = 1:4
P(:,:,n) = P(:,:,n)/sum(sum(P(:,:,n)));
end
%--------------------------------------------------------------------------
%4.对共生矩阵计算能量、熵、惯性矩、相关4个特征值
%--------------------------------------------------------------------------
H = zeros(1,4);
I = H;
Ux = H; Uy = H; %通过传递,将各个
deltaX= H; deltaY = H; %要求的参数初始化
C =H; %为4列的零行向量
for n = 1:4
E(n) = sum(sum(P(:,:,n).^2)); %求角二阶矩
for i = 1:16
for j = 1:16
if P(i,j,n)~=0
H(n) = -P(i,j,n)*log(P(i,j,n))+H(n); %求熵
end
I(n) = (i-j)^2*P(i,j,n)+I(n); %求对比度
Ux(n) = i*P(i,j,n)+Ux(n); %相关性中μx
Uy(n) = j*P(i,j,n)+Uy(n); %相关性中μy
end
end
end
for n = 1:4
for i = 1:16
for j = 1:16
deltaX(n) = (i-Ux(n))^2*P(i,j,n)+deltaX(n); %相关性中σx
deltaY(n) = (j-Uy(n))^2*P(i,j,n)+deltaY(n); %相关性中σy
C(n) = i*j*P(i,j,n)+C(n);
end
end
C(n) = (C(n)-Ux(n)*Uy(n))/deltaX(n)/deltaY(n); %求相关度
end
%显示各个数据,加分号就不显示
E %能量
H %熵
I %对比度
C %相关度
%画图部分,subplot是将一个窗口划分成若干块,绘图函数和参数我用的不同的,
%你对应着看后然后自己选择修改吧。应该能看懂吧?=。=!
figure;
subplot(2,2,1);stem(E,'filled');title('角二阶矩'); %实心
subplot(2,2,2);stem(H);title('熵'); %空心
subplot(2,2,3);stem(I,'c');title('对比度'); %改变颜色,一般用英文首字母小写,如红色r,蓝色b
subplot(224);plot(C);title('相关度'); %普通连线
%作者联系hxze220@hotmail.com