how to enhance a color image ?

Question

Sivakumaran Chandrasekaran 2012-8-22

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/46499-how-to-enhance-a-color-image

编辑： DGM 2024-5-28

For gray image, we use the commands like adapthisteq, imadjust... How to increase the intensity for the color image.

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Image Analyst 2012-8-22

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/46499-how-to-enhance-a-color-image#answer_56876

Convert to hsv color space with rgb2hsv(). Then do those same things on the v channel, then transform back to rgb color space with hsv2rgb().

6 个评论
显示 4更早的评论隐藏 4更早的评论

Sivakumaran Chandrasekaran 2012-8-22

Thanks Image Analyst.. Now, I got your point..

DGM 2023-7-2

编辑：DGM 2024-5-28

在 MATLAB Online 中打开

FWIW, the synopsis for adapthisteq() has had an example of doing this in LAB. That said, it's written around very old conventions, so it can be simplified in contemporary versions. For comparison:

% inputs
inpict = imread('peppers.png');
cl = 0.005;
% adjust V in HSV
hsvpict = rgb2hsv(inpict);
hsvpict(:,:,3) = adapthisteq(hsvpict(:,:,3),'cliplimit',cl); % adjust
op1 = im2uint8(hsv2rgb(hsvpict));
% adjust L in LAB
labpict = rgb2lab(inpict);
labpict(:,:,1) = adapthisteq(labpict(:,:,1)/100,'cliplimit',cl)*100; % adjust
op2 = im2uint8(lab2rgb(labpict));
% display as a montage
outpict = [inpict; op1; op2];
imshow(outpict,'border','tight')

... either way, it might not look so great.

For what it's worth, MIMT has a convenience tool for applying histeq() and adapthisteq() to color images. It's simple to use, preserves the numeric class, and does not require IPT.

% inputs
inpict = imread('peppers.png');
cl = 0.005;
% CLAHE in RGB
op1 = histeqtool(inpict,'ahisteqrgb','cliplimit',cl);
% CLAHE on L in LCHab
op2 = histeqtool(inpict,'ahisteqlchab','cliplimit',cl);
% display as a montage
outpict = [inpict; op1; op2];
imshow(outpict,'border','tight')

Note the differences between the LCHab result using histeqtool() and that achieved using the prior approach using rgb2lab() (e.g. the yellow pepper and other regions near primary/secondary corners of the RGB cube). By default, histeqtool() does chroma truncation prior to conversion back to RGB. That prevents out-of-gamut colors from having their L and H altered when they move back to the gamut boundary. Consequently, the histogram equalization of L is actually preserved, whereas in the IPT-only approach, the histogram equalization of L is not preseved.

请先登录，再进行评论。