Add 05

Author: timerring

05_conversion_smoothing_sharpening_and_segmentation_of_color_images.md

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+# Matlab实现彩色图像的转换、平滑、锐化与分割
+
+## 目的
+
+1. 使用 RGB、索引和灰度级图像间转换的函数
+2. 掌握彩色图像平滑的MATLAB 仿真
+3. 彩色图像锐化
+4. RGB 彩色图像分割
+
+## 内容
+
+### 1.使用 RGB、索引和灰度级图像间转换的函数
+
+```matlab
+clc
+f=imread('D:\pic\DIP3E_CH06\Fig0651(a)(flower_no_compression).tif');
+imshow(f)
+title('原图像');
+
+[X1,map1]=rgb2ind(f,8,'nodither');
+figure
+imshow(X1,map1);%无抖动处理的颜色数减少到8 的图像
+title('无抖动处理的颜色数减少到8 的图像');
+
+[X2,map2]=rgb2ind(f,8,'dither');
+figure
+imshow(X2,map2)%有抖动处理的颜色数减少到8 的图像
+title('有抖动处理的颜色数减少到8 的图像');
+
+g=rgb2gray(f);
+g1=dither(g);
+figure,imshow(g);
+title('使用函数rgb2gray 得到的原图像的灰度级图像');
+figure,imshow(g1);
+title('经抖动处理后的灰度图像（这是一幅二值图像）');
+```
+
+### 2.掌握彩色图像平滑的MATLAB 仿真
+
+```matlab
+function hsi = rgb2hsi(rgb)
+
+rgb=im2double(rgb);
+r=rgb(:,:,1);
+g=rgb(:,:,2);
+b=rgb(:,:,3);
+
+num=0.5*((r-g)+(r-b));
+den=sqrt((r-g).^2+(r-b).*(g-b));
+theta=acos(num./(den+eps));
+
+H=theta;
+H(b>g)=2*pi-H(b>g);
+H=H/(2*pi);
+
+num=min(min(r,g),b);
+den=r+g+b;
+den(den==0)=eps;
+S=1-3.*num./den;
+
+H(S==0)=0;
+I=(r+g+b)/3;
+
+hsi=cat(3,H,S,I);
+
+function rgb=hsi2rgb(hsi)
+H=hsi(:,:,1)*2*pi;
+S=hsi(:,:,2);
+I=hsi(:,:,3);
+
+R=zeros(size(hsi,1),size(hsi,2));
+G=zeros(size(hsi,1),size(hsi,2));
+B=zeros(size(hsi,1),size(hsi,2));
+
+idx=find((0<=H)&(H<2*pi/3));
+B(idx)=I(idx).*(1-S(idx));
+R(idx)=I(idx).*(1-S(idx).*cos(H(idx))./cos(pi/3-H(idx)));
+G(idx)=3*I(idx)-(R(idx)+B(idx));
+
+idx=find((2*pi/3<=H)&(H<4*pi/3));
+R(idx)=I(idx).*(1-S(idx));
+G(idx)=I(idx).*(1+S(idx).*cos(H(idx)-2*pi/3)./cos(pi-H(idx)));
+B(idx)=3*I(idx)-(R(idx)+G(idx));
+
+idx=find((4*pi/3<=H)&(H<=2*pi));
+G(idx)=I(idx).*(1-S(idx));
+B(idx)=I(idx).*(1+S(idx).*cos(H(idx)-4*pi/3)./cos(5*pi/3-H(idx)));
+R(idx)=3*I(idx)-(G(idx)+B(idx));
+
+rgb=cat(3,R,G,B);
+rgb=max(min(rgb,1),0);
+
+%%%%%%%%%%%主函数——图像平滑
+
+clear all
+clc
+fc=imread('D:\pic\DIP3E_CH06\Fig0637(a)(caster_stand_original).tif');
+imshow(fc)
+h=rgb2hsi(fc);
+H=h(:,:,1);%显示h 分量图像
+figure,imshow(H)
+title('H 分量')
+S=h(:,:,2);
+title('S 分量')
+figure,imshow(S)
+I=h(:,:,3);
+figure,imshow(I)
+title('I 分量')
+w=fspecial('average',25);
+I_filtered=imfilter(I,w,'replicate');
+h=cat(3,H,S,I_filtered);
+f=hsi2rgb(h);
+figure,imshow(f)
+f=min(f,1);%RGB images must have values in the range[0,1]
+figure,imshow(f)
+```
+
+### 3.彩色图像锐化
+
+```matlab
+clear all
+clc
+fc=imread('D:\pic\DIP3E_CH06\Fig0637(a)(caster_stand_original).tif');
+imshow(fc)
+
+lapmask=[1 1 1;1 -8 1;1 1 1];
+fen=imsubtract(fc,imfilter(fc,lapmask,'replicate'));
+figure,imshow(fen)
+```
+
+### 4.RGB 彩色图像分割
+
+```matlab
+function [C,m]=covmatrix(X)
+
+[K,n]=size(X);
+X=double(X);
+if n==1
+    C=0; m=x;
+else
+    m=sum(X,1)/K;
+    X=X-m(ones(K,1),:);
+    C=(X'*X)/(K-1);
+    m=m';
+end
+
+function I=colorseg(varargin)
+
+f=varargin{2};
+if(ndims(f)~=3)|(size(f,3)~=3)
+    error('Input image must be RGB!');
+end
+M=size(f,1); N=size(f,2);
+[f,L]=imstack2vectors(f);
+f=double(f);
+I=zeros(M*N,1);
+T=varargin{3};
+m=varargin{4};
+m=m(:)';%make sure that m is a row vetor
+if length(varargin)==4
+    method='euclidean';
+elseif length(varargin)==5
+    method='mahalanobis';
+else
+    error('wrong number of inputs!');
+end
+switch method
+    case 'euclidean'
+        p=length(f);
+        D=sqrt(sum(abs(f-repmat(m,p,1)).^2,2));
+    case 'mahalanobis'
+        C=varargin{5};
+        D=mahalanobis(f,C,m);
+    otherwise
+        error('Unknown segmentation method!');
+end
+
+J=find(D<=T);
+I(J)=1;
+I=reshape(I,M,N);
+
+function [X,R]=imstack2vectors(S,MASK)
+[M,N,n]=size(S);
+if nargin==1
+    MASK=true(M,N);
+else
+    MASK=MASK~=0;
+end
+[I,J]=find(MASK);
+R=[I,J];
+Q=M*N;
+X=reshape(S,Q,n);
+MASK=reshape(MASK,Q,1);
+X=X(MASK,:);
+
+
+%%%%%%RGB 图像分割主程序
+clear all
+clc
+f=imread('D:\pic\DIP3E_CH06\Fig0637(a)(caster_stand_original).tif');
+mask=roipoly(f);
+figure,imshow(mask)%mask 是一幅2 值图像（大小与f 相同）
+red=immultiply(mask,f(:,:,1));
+figure,imshow(red)
+title('red 分量');
+
+green=immultiply(mask,f(:,:,2));
+figure,imshow(green)
+title('green 分量');
+
+blue=immultiply(mask,f(:,:,3));
+figure,imshow(blue)
+title('blue 分量');
+g=cat(3,red,green,blue);
+figure,imshow(g)
+
+%计算ROI 中的点的均值向量和协方差矩阵
+[M,N,K]=size(g);
+I=reshape(g,M*N,3);
+idx=find(mask);
+I=double(I(idx,1:3));
+[C,m]=covmatrix(I);
+
+d=diag(C);
+sd=sqrt(d)'
+E25=colorseg('euclidean',f,25,m);
+%colorseg('m',f,T,m)T 值可取的值为25 的倍数时得到的不同结果
+```
+
+
+
+参考文献：
+
+[1] [Rafael C. Gonzalez, Richard E. Woods, and Steven L. Eddins. 2003. Digital Image Processing Using MATLAB. Prentice-Hall, Inc., USA.](https://github.com/timerring/digital-image-processing-matlab/blob/main/reference/Digital_Image_Processing_Using_Matlab.pdf)
+
+[2] [阮秋琦. 数字图像处理（MATLAB版）\[M\]. 北京：电子工业出版社, 2014.](https://github.com/timerring/digital-image-processing-matlab/blob/main/reference/Digital_Image_Processing_(MATLAB_version).pdf)
+
+[3] [冈萨雷斯. 数字图像处理（第三版）\[M\]. 北京：电子工业出版社, 2011.](https://github.com/timerring/digital-image-processing-matlab/blob/main/reference/Digital_Image_Processing_(Third_Edition).pdf)
+
+
+
+
+
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