完整版真彩色图像处理

第四部分真彩色增强、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⑴、将R , G , B 分量图转化为H , S , I 分量图；⑵、利用对灰度图增强的方法增强其中的I 分量图； ⑶、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W 卜詡|押号鼻）L U（a）增强前图像P ■*口ifl・・・*■曲・（b）增强后图像图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，其代码见附他■如n ? tiw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。

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Eompes-ti in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')% 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);imshow(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);% 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);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 =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 Converts 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 undefined. 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(:, :, 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 = rgb(:, :, 2);b = rgb(:, :, 3);% Implement the conversion equations.num = 0.5*((r - g) + (r - b));den = sqrt((r - g).A2 + (r - b).*(g - b));theta = acos(num./(den + eps));H = theta;H(b > g) = 2*pi - H(b > g);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;% 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(:, :, 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.% Copyright 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);% Implement 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) = 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(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 = max(min(rgb, 1), 0);直接在RGB空间进行图像增强clearclcA=imread( 'C:\Users\liuxinju\Desktop\maomao.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 Component' );% ------ 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' )。