![]() ![]() The answer provided by Bull is the best I have come across so far. display the results (you might also want to see lab_planes before and after). Merge the the color planes back into an Lab imageĬv::cvtColor(lab_image, image_clahe, CV_Lab2BGR) apply the CLAHE algorithm to the L channel READ RGB color image and convert it to LabĬv::Mat bgr_image = cv::imread("image.png") Ĭv::cvtColor(bgr_image, lab_image, CV_BGR2Lab) Ĭv::split(lab_image, lab_planes) // now we have the L image in lab_planes You can read about CLAHE in Graphics Gems IV, pp474-485Īnd here is the C++ that produced the above image, based on, but extended for color. However, as far as I know it is not documented. What you want is OpenCV's CLAHE (Contrast Limited Adaptive Histogram Equalization) algorithm. ![]() Finally convert the resulting Lab back to RGB. Convert the RGB image to Lab color-space (e.g., any color-space with a luminance channel will work fine), then apply adaptive histogram equalization to the L channel.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |