边缘检测(6)Log(Laplacianof Gassian )算子
2014-03-19 21:39
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利用图像强度二阶导数的零交叉点来求边缘点的算法对噪声十分敏感,所以在边缘增强前滤除噪声。为此,马尔(Marr)和希尔得勒斯(Hildreth)根据人类视觉特性提出了一种边缘检测的方法,该方法将高斯滤波和拉普拉斯检测算子结合在一起进行边缘检测的方法,故称为Log(Laplacianof Gassian )算法。也称之为拉普拉斯高斯算法。该算法的主要思路和步骤如下:
I=imread ('lena.bmp');
BW1=edge(I,'log',0.00);
figure,imshow(BW1);
title('阈值为0.00的LOG算子边缘检测图像');
BW11=edge(I,'log',0.05);
figure,imshow(BW11);
title('阈值为0.05的LOG算子边缘检测图像');
BW2= edge(I,'log',0.1);
figure,imshow(BW2);
title('阈值为0.1的LOG算子边缘检测图像');
BW21= edge(I,'log',0.2);
figure,imshow(BW21);
title('阈值为0.2的LOG算子边缘检测图像');
BW22= edge(I,'log',0.3);
figure,imshow(BW22);
title('阈值为0.3的LOG算子边缘检测图像');
I=imread ('lena.bmp');
BW1=edge(I,'log',0.00);
figure,imshow(BW1);
title('阈值为0.00的LOG算子边缘检测图像');
BW11=edge(I,'log',0.05);
figure,imshow(BW11);
title('阈值为0.05的LOG算子边缘检测图像');
BW2= edge(I,'log',0.1);
figure,imshow(BW2);
title('阈值为0.1的LOG算子边缘检测图像');
BW21= edge(I,'log',0.2);
figure,imshow(BW21);
title('阈值为0.2的LOG算子边缘检测图像');
BW22= edge(I,'log',0.3);
figure,imshow(BW22);
title('阈值为0.3的LOG算子边缘检测图像');
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