% 读取原图像
a0=imread('ic.tif');
figure(1)
imshow(a0); %如图6-11所示
%加入高斯噪声
a1=imnoise(a0,'salt & pepper', 0.02);
figure(2)
imshow(a1); %如图6-12所示
%直接进行秩排序膨胀操作
a2=ordfilt2(a1,9, ones(3));
figure(3)
imshow(a2); %如图6-13所示
c0=zeros(256);
c1=zeros(256);
c2=zeros(256);
c3=zeros(256);
c4=zeros(256);
c5=zeros(256);
c6=zeros(256);
c7=zeros(256);
%按照阈值为1进行阈值分解, 进行层叠膨胀
for j=1:255
b=a1;
for i=1:65536
if b(i)>=j
b(i)=1;
else
b(i)=0;
end
end
c0=c0+ im2double(ordfilt2(b,9, ones(3)));
end
c0=im2uint8(c0);
figure(4)
imshow(c0); %如图6-14所示
%按照阈值为2进行阈值分解, 进行层叠膨胀
for j=1:2:255
b=a1;
for i=1:65536
if b(i)>=j
b(i)=1;
else
b(i)=0;
end
end
c1=c1+ im2double(ordfilt2(b,9, ones(3)));
end
c1=im2uint8(c1);
figure(5)
imshow(c1); %如图6-15所示
%直接进行秩统计排序腐蚀操作
a3= ordfilt2(a1,1, ones(3));
figure(6)
imshow(a3); %如图6-16所示
%按照阈值为1进行阈值分解, 进行层叠腐蚀
for j=1:255
b=a1;
for i=1:65536
if b(i)>=j
b(i)=1;
else
b(i)=0;
end
end
c2=c2+ im2double(ordfilt2(b,1, ones(3)));
end
c2=im2uint8(c2);
figure(7)
imshow(c2); %如图6-17所示
%按照阈值为2进行阈值分解, 进行层叠腐蚀
for j=1:2:255
b=a1;
for i=1:65536
if b(i)>=j
b(i)=1;
else
b(i)=0;
end
end
c3=c3+ im2double(ordfilt2(b,1, ones(3)));
end
c3=im2uint8(c3);
figure(8)
imshow(c3); %如图6-18所示
%直接进行开操作
a4= ordfilt2(a3,9, ones(3))
figure(9)
imshow(a4); %如图6-19所示
%按照阈值为1进行阈值分解, 进行层叠开操作
for j=1:255
b=c2;
for i=1:65536
if b(i)>=j
b(i)=1;
else
b(i)=0;
end
end
c4=c4+ im2double(ordfilt2(b,9, ones(3)));
end
c4=im2uint8(c4);
figure(10)
imshow(c4); %如图6-20所示
%按照阈值为2进行阈值分解, 进行层叠开操作
for j=1:2:255
b=c3;
for i=1:65536
if b(i)>=j
b(i)=1;
else
b(i)=0;
end
end
c5=c5+ im2double(ordfilt2(b,9, ones(3)));
end
c5=im2uint8(c5);
figure(11)
imshow(c5); %如图6-21所示
%直接进行闭操作
a5= ordfilt2(a2, 1, ones(3));
figure(12)
imshow(a5); %如图6-22所示
%按照阈值为1进行阈值分解, 进行层叠闭操作
for j=1:255
b=c0;
for i=1:65536
if b(i)>=j
b(i)=1;
else
b(i)=0;
end
end
c6=c6+ im2double(ordfilt2(b,1, ones(3)));
end
c6=im2uint8(c6);
figure(13)
imshow(c6); %如图6-23所示
%按照阈值为2进行阈值分解, 进行层叠闭操作
for j=1:2:255
b=c1;
for i=1:65536
if b(i)>=j
b(i)=1;
else
b(i)=0;
end
end
c7=c7+ im2double(ordfilt2(b,1, ones(3)));
end
c7=im2uint8(c7);
figure(14)
imshow(c7); %如图6-24所示
matlab-image-processing.rar_matlab bridge.bmp
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matlab-image-processing.rar_matlab bridge.bmp （139个子文件） 
figure46.asv 74B
PEPPERS.BMP 257KB LENA.BMP 257KB spine_surf_small.bmp 65KB skullcar_high4_small.bmp 65KB VRTabdomen_small1.bmp 65KB mrbrain_stanford_small.bmp 65KB skkkull_surf_small.bmp 65KB ribs_and_corcalc_small.bmp 65KB mrbrain_3_small.bmp 65KB Girl.bmp 65KB spine.bmp 65KB brain.bmp 65KB Couple.bmp 65KB nephogram.bmp 65KB Bridge.bmp 65KB LENA256.BMP 65KB Q1.BMP 65KB Q5.BMP 65KB Q2.BMP 65KB Q4.BMP 65KB Q3.BMP 65KB Q7.BMP 65KB XIN.DAT 180KB XIN10.DAT 60KB XIN1.DAT 60KB XD10.DAT 60KB stackmor.m 3KB design4x512.m 3KB all_medfilt2.m 2KB encode.m 2KB wmedfilt1.m 2KB sgomedwmedfilt.m 2KB filfs.m 1KB DILATEERODE.m 1KB sfnncl.m 1KB ordtest.m 1KB stack.m 969B stackmed.m 969B fsamfir.m 969B figure12.m 952B conv2p.m 792B test.m 779B med2simulation.m 774B fwindfir.m 728B klencode.m 680B fftencode.m 668B wavep.m 663B test.m 640B figure18.m 612B fwindfirelse.m 592B HTencode.m 575B DCTencode.m 572B figure2.m 535B figure16.m 508B figure14.m 499B figure15.m 469B fwindfirhan.m 454B lut.m 450B fwindfirham.m 445B ftranfir.m 438B fwindfirbox.m 421B bwexam.m 420B figure13.m 416B figure10.m 394B figure17.m 346B p81.m 336B fwind2fir.m 321B med2test.m 284B pho1.m 260B flterter.m 240B test.m 237B p62.m 232B p47-2.m 221B maytest.m 219B tyu.m 213B p64.m 202B figure7.m 193B figure62.m 186B figure13.m 184B p54.m 169B figure1.m 155B figure21.m 152B figure4.m 146B figure6.m 139B figure9.m 138B figure42.m 134B figure41.m 128B figure20.m 124B p49.m 121B figure48.m 119B figure11.m 119B p58.m 118B figure18.m 115B figure12.m 114B figure19.m 105B figure38.m 102B figure51.m 101B bwtest.m 100B figure16.m 99B共 139 条
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