How to apply CLAHE on RGB color images

Question

CLAHE is Contrast Limited Adaptive Histogram Equalization and a source in C can be found at http://tog.acm.org/resources/GraphicsGems/gemsiv/clahe.c

So far I have only seen some examples/tutorials about applying CLAHE on grayscale images so is it possible to apply CLAHE on color images (such as RGB 3 channles images)? If yes, how?

not possible directly. maybe convert to LAB or HSV, apply clahe on L and convert back. and you can use it from [opencv](http://answers.opencv.org/question/12024/use-of-clahe/), too. — berak, Jul 29 '14 at 05:05
possible duplicate of [simple illumination correction in images openCV c++](http://stackoverflow.com/questions/24341114/simple-illumination-correction-in-images-opencv-c) — Bull, Jul 29 '14 at 06:09
This link will help you https://stackoverflow.com/questions/24341114/simple-illumination-correction-in-images-opencv-c — gameon67, Nov 22 '18 at 02:07

score 59 · Answer 1 · edited Nov 19 '17 at 03:47

59

Conversion of RGB to LAB(L for lightness and a and b for the color opponents green–red and blue–yellow) will do the work. Apply CLAHE to the converted image in LAB format to only Lightness component and convert back the image to RGB. Here is the snippet.

bgr = cv2.imread(image_path)

lab = cv2.cvtColor(bgr, cv2.COLOR_BGR2LAB)

lab_planes = cv2.split(lab)

clahe = cv2.createCLAHE(clipLimit=2.0,tileGridSize=(gridsize,gridsize))

lab_planes[0] = clahe.apply(lab_planes[0])

lab = cv2.merge(lab_planes)

bgr = cv2.cvtColor(lab, cv2.COLOR_LAB2BGR)

bgr is the final RGB image obtained after applying CLAHE.

edited Nov 19 '17 at 03:47

rinkert

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answered Nov 18 '17 at 20:18

Nikhil V M

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`cv2.split` isn't required as OpenCV in Python uses NumPy arrays. Once you create the CLAHE object, just do `lab[...,0] = clahe.apply(lab[...,0])`. You can also remove `cv2.merge` – rayryeng Jul 03 '19 at 04:02
This method sometimes gives bad results. See point 4 of https://stackoverflow.com/questions/56905592/optimize-the-contrast-brightness-or-histogram-equalization-of-a-color-photo-of. Would you have any idea @NikhilVM? – Basj Jul 06 '19 at 08:30
@Basj One has to try varying the parameters `clipLimit` and `tileGridSize`. In the question linked above, the OP has used grid size of 100. – Jeru Luke May 07 '22 at 18:59

score 4 · Answer 2 · answered Jul 06 '22 at 15:48

img = cv2.imread(img_path, cv2.IMREAD_COLOR)
img = cv2.cvtColor(img, cv2.COLOR_RGB2Lab)

#configure CLAHE
clahe = cv2.createCLAHE(clipLimit=10,tileGridSize=(8,8))

#0 to 'L' channel, 1 to 'a' channel, and 2 to 'b' channel
img[:,:,0] = clahe.apply(img[:,:,0])

img = cv2.cvtColor(img, cv2.COLOR_Lab2RGB)

cv2.imshow("image", img)
cv2.waitKey(0)
cv2.destroyAllWindows()

score 1 · Answer 3 · answered Jun 01 '21 at 10:53

this for c#, apply clahe for rgb images.

    private static Image<Bgr, byte> appy_CLAHE( Image<Bgr, byte> imgIn , int clipLimit=2, int tileSize=25)
    {
        var imglabcol = new Image<Lab, byte>(imgIn.Size);
        var imgoutL = new Image<Gray, byte>(imgIn.Size);  

        var imgoutBGR = new Image<Bgr, byte>(imgIn.Size);  

        //clahe filter must be applied on luminance channel or grayscale image
        CvInvoke.CvtColor(imgIn, imglabcol, ColorConversion.Bgr2Lab, 0); 

        CvInvoke.CLAHE(imglabcol[0], clipLimit, new Size(tileSize, tileSize), imgoutL);
        imglabcol[0] = imgoutL; // write clahe results on Lum channel into image

        CvInvoke.CvtColor(imglabcol, imgoutBGR, ColorConversion.Lab2Bgr, 0);

        return imgoutBGR;
    }

How to apply CLAHE on RGB color images

3 Answers3

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