matlab中图像锐化程序怎么写，简单点，最好有注释。

%之前写的一个程序，这里面用Sobel算子和Prewitt算子的部分就是对图像锐化得到边缘的了。也可以直接用matlab自带的函数S = edge(I, 'sobel')进行锐化。

clc

close all

clear all

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%读入图像

f=imread('Pictures/4_m03.tif')

%f=imread('Pictures/5_m01.tif')

%f=imread('Pictures/10_m02.tif')

%f=imread('Pictures/22_m03.tif')

f=imresize(f,0.25)

f=im2double(f)

[m,n]=size(f)

subplot(2,3,1),imshow(f)

title('原始图像')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%生成高斯平滑滤波模板

hg=zeros(3,3)  %设定模板大小3*3

delta=0.5

for x=1:1:3

    for y=1:1:3

        u=x-2

        v=y-2

   谨带     hg(x,y)=exp(-(u^2+v^2)/(2*pi*delta^2))

    end

end

h=hg/sum(hg(:))

%高斯滤波

ftemp=zeros(m,n)

rowhigh=m-1

colhigh=n-1

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        mod=[f(x-1,y-1) f(x-1,y) f(x-1,y+1) f(x,y-1) f(x,y) f(x,y+1)f(x+1,y-1) f(x+1,y) f(x+1,y+1)]

    竖迹    A=h.*mod

        ftemp(x,y)=sum(A(:))

    end

end

f=ftemp

subplot(2,3,4),imshow(f)

title('高斯滤波后的图像')

 

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%利用Sobel算子进行边缘检测

sx=[-1 0 1-2 0 2-1 0 1]

sy=[-1 -2 -10 0 01 2 1]

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        mod=[f(x-1,y-1) f(x-1,y) f(x-1,y+1) 祥纤芦f(x,y-1) f(x,y) f(x,y+1)f(x+1,y-1) f(x+1,y) f(x+1,y+1)]

        fsx=sx.*mod

        fsy=sy.*mod

        ftemp(x,y)=max((abs(sum(fsx(:)))),(abs(sum(fsy(:)))))

    end

end

fs=im2uint8(ftemp)

subplot(2,3,2),imshow(fs)

title('Sobel算子进行边缘检测的原始图像')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%阈值分割

TH1=140  %设定阈值

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        if (fs(x,y)>=TH1)&((fs(x,y-1) <= fs(x,y)) & (fs(x,y) > fs(x,y+1)) )

          fs(x,y)=200

      elseif(fs(x,y)>=TH1)&( (fs(x-1,y) <=fs(x,y)) & (fs(x,y) >fs(x+1,y)))

          fs(x,y)=200

      else fs(x,y)=50

        end

    end

end

subplot(2,3,5),imshow(fs)

title('Sobel算子边缘检测并细化后的图像')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%利用Prewitt算子进行边缘检测

sx=[1 0 -11 0 -11 0 -1]

sy=[-1 -1 -10 0 01 1 1]

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        mod=[f(x-1,y-1) f(x-1,y) f(x-1,y+1) f(x,y-1) f(x,y) f(x,y+1)f(x+1,y-1) f(x+1,y) f(x+1,y+1)]

        fsx=sx.*mod

        fsy=sy.*mod

        ftemp(x,y)=max((abs(sum(fsx(:)))),(abs(sum(fsy(:)))))

    end

end

fs=im2uint8(ftemp)

subplot(2,3,3),imshow(fs)

title('Prewitt算子进行边缘检测的原始图像')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%阈值分割

TH1=100  %设定阈值

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        if (fs(x,y)>=TH1)&((fs(x,y-1) <= fs(x,y)) & (fs(x,y) > fs(x,y+1)) )

          fs(x,y)=200

      elseif(fs(x,y)>=TH1)&( (fs(x-1,y) <=fs(x,y)) & (fs(x,y) >fs(x+1,y)))

          fs(x,y)=200

      else fs(x,y)=50

        end

    end

end

subplot(2,3,6),imshow(fs)

title('Prewitt算子边缘检测并细化后的图像')

%%%目测大岩含你的是拉普拉斯算子 下面的程序也是一滚笑样的 你试试 图片改成你的图片

A=imread('lena.bmp')

figure(1)

subplot(1,2,1)

imshow(A)

title('原图')

I=double(A)

h=[-1 -1 -1-1 9 -1-1 -1 -1]

J=conv2(I,h,'same')

K=uint8(J)

subplot(1,2,2)

imshow(K)

title('使用拉普拉斯算子锐化枣陪处理后的图')

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