1.灰度变换增强程序：
% GRAY TRANSFORM
clc;
I=imread(\'pout.tif\');
imshow(I);
J=imadjust(I,[0.3 0.7],[0 1],1);
figure;
imshow(J);
J=imadjust(I,[0.3 0.7],[0 1],0.5);
%output values.
figure;
imshow(J);
J=imadjust(I,[0.3 0.7],[0 1],1.5); % if GAMMA is greater than 1,the mapping si weighted toward lower (darker)
figure;
imshow(J);
J=imadjust(I,[0.3 0.7],[0 1],1.5);
%output values.
figure;
imshow(J)
J=imadjust(I,[0.3 0.7],[0 1],1); % If TOP<BOTTOM,the output image is reversed,as in a photographic negative.
figure;
imshow(J);
figure;
imshow(J)
J=imadjust(I,[0.3 0.7],[0 1],1);
figure;
imshow(J);
2.直方图灰度变换
%直方图灰度变换
[X,map]=imread(\'forest.tif\');
I=ind2gray(X,map);%把索引图像转换为灰度图像
imshow(I);
title(\'原图像\');
improfile%用鼠标选择一条对角线，显示线段的灰度值
figure;subplot(121)
plot(0:0.01:1,sqrt(0:0.01:1))
axis square
title(\'平方根灰度变换函数\')
subplot(122)
maxnum=double(max(max(I)));%取得二维数组最大值
J=sqrt(double(I)/maxnum);%把数据类型转换成double,然后进行平方根变换
%sqrt函数不支持uint8类型
J=uint8(J*maxnum);%把数据类型转换成uint8类型
imshow(J)
title(\'平方根变换后的图像\')
[X,map]=imread(\'forest.tif\');
I=ind2gray(X,map);%把索引图像转换为灰度图像
imshow(I);
title(\'原图像\');
improfile%用鼠标选择一条对角线，显示线段的灰度值
figure;subplot(121)
plot(0:0.01:1,sqrt(0:0.01:1))
axis square
title(\'平方根灰度变换函数\')
subplot(122)
maxnum=double(max(max(I)));%取得二维数组最大值
J=sqrt(double(I)/maxnum);%把数据类型转换成double,然后进行平方根变换
%sqrt函数不支持uint8类型
J=uint8(J*maxnum);%把数据类型转换成uint8类型
imshow(J)
title(\'平方根变换后的图像\')
3.直方图均衡化程序举例
% HISTGRAM EAQUALIZATION
clc;
% Clear command window
I=imread(\'tire.tif\');
% reads the image in tire.tif into I
imshow(I);
% displays the intensity image I with 256 gray levels
figure;
%creates a new figure window
imhist(I);
% displays a histogram for the intensity image I
J=histeq(I,64);
% transforms the intensity image I,returning J an intensity
figure;
%image with 64 discrete levels
imshow(J);
figure;
imhist(J);
J=histeq(I,32);
%transforms the intensity image ,returning in % J an intensity
figure;
%image with 32 discrete levels
imshow(J);
figure;
imhist(J);
clc;
% Clear command window
I=imread(\'tire.tif\');
% reads the image in tire.tif into I
imshow(I);
% displays the intensity image I with 256 gray levels
figure;
%creates a new figure window
imhist(I);
% displays a histogram for the intensity image I
J=histeq(I,64);
% transforms the intensity image I,returning J an intensity
figure;
%image with 64 discrete levels
imshow(J);
figure;
imhist(J);
J=histeq(I,32);
%transforms the intensity image ,returning in % J an intensity
figure;
%image with 32 discrete levels
imshow(J);
figure;
imhist(J);
4.直方图规定化程序举例
% HISTGRAM REGULIZATION
clc;
clc;
%Clear command window
I=imread(\'tire.tif\');
%reads the image in tire.tif into I
J=histeq(I,32);
%transforms the intensity image I,returning in
%J an intensity image with 32 discrete levels
[counts,x]=imhist(J);
%displays a histogram for the intensity image I
Q=imread(\'pout.tif\');
%reads the image in tire.tif into I
figure;
imshow(Q);
figure;
imhist(Q);
M=histeq(Q,counts);
%transforms the intensity image Q so that the
%histogram of the output image M approximately matches counts
figure;
imshow(M);
figure;
imhist(M);
I=imread(\'tire.tif\');
%reads the image in tire.tif into I
J=histeq(I,32);
%transforms the intensity image I,returning in
%J an intensity image with 32 discrete levels
[counts,x]=imhist(J);
%displays a histogram for the intensity image I
Q=imread(\'pout.tif\');
%reads the image in tire.tif into I
figure;
imshow(Q);
figure;
imhist(Q);
M=histeq(Q,counts);
%transforms the intensity image Q so that the
%histogram of the output image M approximately matches counts
figure;
imshow(M);
figure;
imhist(M);
空域滤波增强部分程序
1.线性平滑滤波
I=imread(\'eight.tif\');
J=imnoise(I,\'salt & pepper\',0.02);
subplot(221),imshow(I)
title(\'原图像\')
subplot(222),imshow(J)
title(\'添加椒盐噪声图像\')
K1=filter2(fspecial(\'average\',3),J)/255;%应用3*3邻域窗口法
subplot(223),imshow(K1)
title(\'3x3窗的邻域平均滤波图像\')
K2=filter2(fspecial(\'average\',7),J)/255;%应用7*7邻域窗口法
subplot(224),imshow(K2)
title(\'7x7窗的邻域平均滤波图像\')
I=imread(\'eight.tif\');
J=imnoise(I,\'salt & pepper\',0.02);
subplot(221),imshow(I)
title(\'原图像\')
subplot(222),imshow(J)
title(\'添加椒盐噪声图像\')
K1=filter2(fspecial(\'average\',3),J)/255;%应用3*3邻域窗口法
subplot(223),imshow(K1)
title(\'3x3窗的邻域平均滤波图像\')
K2=filter2(fspecial(\'average\',7),J)/255;%应用7*7邻域窗口法
subplot(224),imshow(K2)
title(\'7x7窗的邻域平均滤波图像\')
2.中值滤波器
MATLAB中的二维中值滤波函数medfit2来进行图像中椒盐躁声的去除
%IMAGE NOISE REDUCTION WITH MEDIAN FILTER
clc;
hood=3;%滤波窗口
[I,map]=imread(\'eight.tif\');
imshow(I,map);
noisy=imnoise(I,\'salt & pepper\',0.05);
figure;
imshow(noisy,map);
filtered1=medfilt2(noisy,[hood hood]);
figure;
imshow(filtered1,map);
hood=5;
filtered2=medfilt2(noisy,[hood hood]);
figure;
imshow(filtered2,map);
hood=7;
filtered3=medfilt2(noisy,[hood hood]);
figure;
imshow(filtered3,map);
MATLAB中的二维中值滤波函数medfit2来进行图像中椒盐躁声的去除
%IMAGE NOISE REDUCTION WITH MEDIAN FILTER
clc;
hood=3;%滤波窗口
[I,map]=imread(\'eight.tif\');
imshow(I,map);
noisy=imnoise(I,\'salt & pepper\',0.05);
figure;
imshow(noisy,map);
filtered1=medfilt2(noisy,[hood hood]);
figure;
imshow(filtered1,map);
hood=5;
filtered2=medfilt2(noisy,[hood hood]);
figure;
imshow(filtered2,map);
hood=7;
filtered3=medfilt2(noisy,[hood hood]);
figure;
imshow(filtered3,map);
3. 4邻域8邻域平均滤波算法
% IMAGE NOISE REDUCTION WITH MEAN ALGORITHM
clc;
[I,map]=imread(\'eight.tif\');
noisy=imnoise(I,\'salt & pepper\',0.05);
myfilt1=[0 1 0;1 1 1;0 1 0];%4邻域平均滤波模版
myfilt1=myfilt1/9;%对模版归一化
filtered1=filter2(myfilt1,noisy);
imshow(filtered1,map);
myfilt2=[1 1 1;1 1 1;1 1 1];
myfilt2=myfilt2/9;
filtered2=filter2(myfilt2,noisy);
figure;
imshow(filtered2,map);
% IMAGE NOISE REDUCTION WITH MEAN ALGORITHM
clc;
[I,map]=imread(\'eight.tif\');
noisy=imnoise(I,\'salt & pepper\',0.05);
myfilt1=[0 1 0;1 1 1;0 1 0];%4邻域平均滤波模版
myfilt1=myfilt1/9;%对模版归一化
filtered1=filter2(myfilt1,noisy);
imshow(filtered1,map);
myfilt2=[1 1 1;1 1 1;1 1 1];
myfilt2=myfilt2/9;
filtered2=filter2(myfilt2,noisy);
figure;
imshow(filtered2,map);
频域增强程序举例
1.低通滤波器
% LOWPASS FILTER
clc;
[I,map]=imread(\'eight.tif\');
noisy=imnoise(I,\'gaussian\',0.05);
imshow(noisy,map);
myfilt1=[1 1 1;1 1 1;1 1 1];
myfilt1=myfilt1/9;
filtered1=filter2(myfilt1,noisy);
figure;
imshow(filtered1,map);
myfilt2=[1 1 1;1 2 1;1 1 1];
myfilt2=myfilt2/10;
filtered2=filter2(myfilt2,noisy);
figure;
imshow(filtered2,map);
myfilt3=[1 2 1;2 4 2; 1 2 1];
myfilt3=filter2(myfilt3,noisy);
figure;
imshow(filtered3,map);
% LOWPASS FILTER
clc;
[I,map]=imread(\'eight.tif\');
noisy=imnoise(I,\'gaussian\',0.05);
imshow(noisy,map);
myfilt1=[1 1 1;1 1 1;1 1 1];
myfilt1=myfilt1/9;
filtered1=filter2(myfilt1,noisy);
figure;
imshow(filtered1,map);
myfilt2=[1 1 1;1 2 1;1 1 1];
myfilt2=myfilt2/10;
filtered2=filter2(myfilt2,noisy);
figure;
imshow(filtered2,map);
myfilt3=[1 2 1;2 4 2; 1 2 1];
myfilt3=filter2(myfilt3,noisy);
figure;
imshow(filtered3,map);
2.布特沃斯低通滤波器图像实例
I=imread(\'saturn.png\');
J=imnoise(I,\'salt & pepper\',0.02);
subplot(121),imshow(J)
title(\'含噪声的原图像\')
J=double(J);
f=fft2(J);
g=fftshift(f);
[M,N]=size(f);
n=3;d0=20;
n1=floor(M/2);n2=floor(N/2);
for i=1:M;
for j=1:N;
d=sqrt((i-n1)^2+(j-n2)^2);
h=1/(1+0.414*(d/d0)^(2*n));
g(i,j)=h*g(i,j);
end
end
g=ifftshift(g);
g=uint8(real(ifft2(g)));
subplot(122),imshow(g)
title(\'三阶Butterworth滤波图像\')
I=imread(\'saturn.png\');
J=imnoise(I,\'salt & pepper\',0.02);
subplot(121),imshow(J)
title(\'含噪声的原图像\')
J=double(J);
f=fft2(J);
g=fftshift(f);
[M,N]=size(f);
n=3;d0=20;
n1=floor(M/2);n2=floor(N/2);
for i=1:M;
for j=1:N;
d=sqrt((i-n1)^2+(j-n2)^2);
h=1/(1+0.414*(d/d0)^(2*n));
g(i,j)=h*g(i,j);
end
end
g=ifftshift(g);
g=uint8(real(ifft2(g)));
subplot(122),imshow(g)
title(\'三阶Butterworth滤波图像\')
色彩增强程序举例
1.真彩色增强实例：
%真彩色图像的分解
clc;
RGB=imread(\'peppers.png\');
subplot(221),imshow(RGB)
title(\'原始真彩色图像\')
subplot(222),imshow(RGB(:,:,1))
title(\'真彩色图像的红色分量\')
subplot(223),imshow(RGB(:,:,2))
title(\'真彩色图像的绿色分量\')
subplot(224),imshow(RGB(:,:,3))
title(\'真彩色图像的蓝色分量\')
%真彩色图像的分解
clc;
RGB=imread(\'peppers.png\');
subplot(221),imshow(RGB)
title(\'原始真彩色图像\')
subplot(222),imshow(RGB(:,:,1))
title(\'真彩色图像的红色分量\')
subplot(223),imshow(RGB(:,:,2))
title(\'真彩色图像的绿色分量\')
subplot(224),imshow(RGB(:,:,3))
title(\'真彩色图像的蓝色分量\')
2.伪彩色增强举例：
I=imread(\'cameraman.tif\');
imshow(I);
X=grayslice(I,16);%thresholds the intensity image I using
%threshold values 1/16,2/16,…..,15/16,returning an indexed %image in X
figure;
imshow(X,hot(16));
I=imread(\'cameraman.tif\');
imshow(I);
X=grayslice(I,16);%thresholds the intensity image I using
%threshold values 1/16,2/16,…..,15/16,returning an indexed %image in X
figure;
imshow(X,hot(16));
3.假彩色增强处理程序举例
[RGB]=imread(\'ghost.bmp\');
imshow(RGB);
RGBnew(:,:,1)=RGB(:,:,3);
RGBnew(:,:,2)=RGB(:,:,1);
RGBnew(:,:,3)=RGB(:,:,2);
figure;
subplot(121);
imshow(RGB);
subplot(122);
imshow(RGBnew);
[RGB]=imread(\'ghost.bmp\');
imshow(RGB);
RGBnew(:,:,1)=RGB(:,:,3);
RGBnew(:,:,2)=RGB(:,:,1);
RGBnew(:,:,3)=RGB(:,:,2);
figure;
subplot(121);
imshow(RGB);
subplot(122);
imshow(RGBnew);
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