真彩色图像处理

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1、第四部分 真彩色增强彩色图像（RGB）RGB模型变换为HSI模型色调H亮度I饱和度S直方图修改HSI模型变换为RGB模型增强的彩色图像RGB一、真彩色增强方法 图4.1 真彩色增强原理图1、 对HSI图像亮度增强、将R，G，B分量图转化为H，S，I分量图；、利用对灰度图增强的方法增强其中的I分量图；、再将结果转化为用R，G，B分量图来显示。以上方法并不改变原图的彩色内容，但增强后的图看起来会有些不同。这是因为尽管色调和饱和度没有变化，但亮度分量得到了增强，整个图会比原来更亮一些。图4.3是基于matlab以增强亮度的方法进行真彩色增强的图像，其代码见附录（a） 增强前图像 （b） 增强后图像

2、图4.2 对HSI进行亮度增强结果结论：图（b）明显比图（a）要亮的多，在视觉效果上，图（b）比较让人觉得美好。2、 对HSI图像进行对比度增强图4.4是基于matlab以增强对比度的方法进行真彩色增强的图像，其代码见附录图4.3 对HSI增强对比度增强的 结论：图（b）的视觉效果明显比图（a）要好的多，清晰的多，颜色比（a）要深。3、 对HSI图像进行亮度和饱和度的增强图4.5是基于matlab以增强亮度和饱和度的方法进行真彩色增强的图像，其代码见附录图4.4 对HSI图像进行增强结果结论：这是对前两个方法的综合， 很显然，图（b）比图（a）要亮，要清晰，视觉效果比以上两种方法分别做要好的多

3、。 二、 直接在rgb空间对图像增强 图4.6是基于matlab在rgb空间增强图像，其代码见附录 图4.5 对RGB图像进行增强结果以下是基于matlab以增强亮度的方法进行真彩色增强的代码：% 彩色图像亮度增强 （执行速度较慢）clcclearfc = imread(E:maomao.jpg);figure(1);imshow(fc)title(原始真彩色（256*256*256色）图像)fr = fc(:,:,1);fg = fc(:,:,2);fb = fc(:,:,3); % imshow(fr)% title(红色分量图像)% imshow(fg)% title(绿色分量图像)%

4、imshow(fb)% title(蓝色分量图像) h = rgb2hsi(fc);H = h(:,:,1);S = h(:,:,2);I = h(:,:,3);I =I*1.5;% imshow(H)% title(色调分量图像)% imshow(S)% title(饱和度分量图像)% imshow(I)% title(亮度分量图像)h = cat(3,H,S,I);%cat函数是拼接数组的函数，这里将在第3维上进行拼接。f = hsi2rgb(h);%增强亮度分量后的rgb图像f = min(f,1);%保证元素值最大为1,因为按公式转换为rgb后可能出现大于1的情况figure(2);i

5、mshow(f)title(仅增强HSI图像的亮度分量所得到的RGB图像)基于matlab以增强对比度的方法进行真彩色增强代码：% 例6.8 彩色图像亮度增强 （执行速度较慢）clcclearfc = imread(I:maomao.jpg);figure(1);imshow(fc)title(原始真彩色（256*256*256色）图像)fr = fc(:,:,1);fg = fc(:,:,2);fb = fc(:,:,3); % imshow(fr)% title(红色分量图像)% imshow(fg)% title(绿色分量图像)% imshow(fb)% title(蓝色分量图像) h

6、= rgb2hsi(fc);H = h(:,:,1);S = h(:,:,2);I = h(:,:,3);S=S*2.0;% imshow(H)% title(色调分量图像)% imshow(S)% title(饱和度分量图像)% imshow(I)% title(亮度分量图像)h = cat(3,H,S,I);%cat函数是拼接数组的函数，这里将在第3维上进行拼接。f = hsi2rgb(h);%增强亮度分量后的rgb图像f = min(f,1);%保证元素值最大为1,因为按公式转换为rgb后可能出现大于1的情况figure(2);imshow(f)title(增强HSI图像的对比度所得到的

7、RGB图像)基于matlab以增强亮度和饱和度的方法进行真彩色增强的图像% 例6.8 彩色图像亮度增强 （执行速度较慢）clcclearfc = imread(I:maomao.jpg);figure(1);imshow(fc) fr = fc(:,:,1);fg = fc(:,:,2);fb = fc(:,:,3); % imshow(fr)% title(红色分量图像)% imshow(fg)% title(绿色分量图像)% imshow(fb)% title(蓝色分量图像)h = rgb2hsi(fc);H = h(:,:,1);S = h(:,:,2);I = h(:,:,3);I =

8、I*2.0;S =S*2.0;% imshow(H)% title(色调分量图像)% imshow(S)% title(饱和度分量图像)% imshow(I)% title(亮度分量图像)h = cat(3,H,S,I);%cat函数是拼接数组的函数，这里将在第3维上进行拼接。f = hsi2rgb(h);%增强亮度分量后的rgb图像f = min(f,1);%保证元素值最大为1,因为按公式转换为rgb后可能出现大于1的情况figure(2);imshow(f)rgb图像转化为hsi图像的代码：rgb2hsi(rgb)function hsi = rgb2hsi(rgb)%RGB2HSI Co

9、nverts an RGB image to HSI.% HSI = RGB2HSI(RGB) converts an RGB image to HSI. The input image% is assumed to be of size M-by-N-by-3, where the third dimension% accounts for three image planes: red, green, and blue, in that% order. If all RGB component images are equal, the HSI conversion% is undefin

10、ed. The input image can be of class double (with values% in the range 0, 1), uint8, or uint16. % The output image, HSI, is of class double, where:% hsi(:, :, 1) = hue image normalized to the range 0, 1 by% dividing all angle values by 2*pi. % hsi(:, :, 2) = saturation image, in the range 0, 1.% hsi(

11、:, :, 3) = intensity image, in the range 0, 1.% Copyright 2002-2004 R. C. Gonzalez, R. E. Woods, & S. L. Eddins% Digital Image Processing Using MATLAB, Prentice-Hall, 2004% $Revision: 1.5 $ $Date: 2005/01/18 13:44:59 $% Extract the individual component images.rgb = im2double(rgb);r = rgb(:, :, 1);g

12、= rgb(:, :, 2);b = rgb(:, :, 3); % Implement the conversion equations.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 =

13、0) = 0; I = (r + g + b)/3;% Combine all three results into an hsi image.hsi = cat(3, H, S, I);hsi图像转化为rgb图像的代码：hsi2rgb(hsi)function rgb = hsi2rgb(hsi)%HSI2RGB Converts an HSI image to RGB.% RGB = HSI2RGB(HSI) converts an HSI image to RGB, where HSI is% assumed to be of class double with: % hsi(:, :,

14、 1) = hue image, assumed to be in the range% 0, 1 by having been divided by 2*pi.% hsi(:, :, 2) = saturation image, in the range 0, 1.% hsi(:, :, 3) = intensity image, in the range 0, 1.% The components of the output image are:% rgb(:, :, 1) = red.% rgb(:, :, 2) = green.% rgb(:, :, 3) = blue.% Copyr

15、ight 2002-2004 R. C. Gonzalez, R. E. Woods, & S. L. Eddins% Digital Image Processing Using MATLAB, Prentice-Hall, 2004% $Revision: 1.5 $ $Date: 2003/10/13 01:01:06 $% Extract the individual HSI component images.hsi=im2double(hsi);H = hsi(:, :, 1) * 2 * pi;S = hsi(:, :, 2);I = hsi(:, :, 3);% Implemen

16、t the conversion equations.R = zeros(size(hsi, 1), size(hsi, 2);G = zeros(size(hsi, 1), size(hsi, 2);B = zeros(size(hsi, 1), size(hsi, 2);% RG sector (0 = H 2*pi/3).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

17、) = 3*I(idx) - (R(idx) + B(idx); % BG sector (2*pi/3 = H 4*pi/3).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);% BR sector.idx = find( (4*pi/3 = H) & (H = 2*pi);G

18、(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); % Combine all three results into an RGB image. Clip to 0, 1 to% compensate for floating-point arithmetic rounding effects.rgb = cat(3, R, G, B);rgb = ma

19、x(min(rgb, 1), 0);直接在RGB空间进行图像增强clearclcA=imread(C:UsersliuxinjuDesktopmaomao.jpg);%读入原始RGB图像whos;figure;imshow(A):title(original image);%显示图像r c d=size(A);%计算图像大小%-计算红色分量并显示分解图-%red(:,:,1)=A(:,:,1);red(:,:,2)=zeros(r,c);red(:,:,3)=zeros(r,c);red=uint8(red*2.0);whos;figure;imshow(red)title(Red Compo

20、nent);%-计算绿色分量并显示分解图-%green(:,:,2)=A(:,:,2);green(:,:,1)=zeros(r,c);green(:,:,3)=zeros(r,c);green=uint8(green*2.0);figure;imshow(green)title(Green Component);%-计算蓝色分量并显示分解图-%blue(:,:,3)=A(:,:,3);blue(:,:,1)=zeros(r,c);blue(:,:,2)=zeros(r,c);blue=uint8(blue*2.0);figure;imshow(blue)title(Blue Component); %-合成-%B(:,:,1)=red(:,:,1);B(:,:,2)=green(:,:,2);B(:,:,3)=blue(:,:,3);figure;imshow(B):title(composition image)