Dear All, The following is an example given in opencv regarding applying Contrast Limited Adaptive Histogram Equalization (CLAHE) *import numpy as np* *import cv2* *img = cv2.imread('tsukuba_l.png',0)* *clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))* *cl1 = clahe.apply(img)* Here the parameter clipLimit =2.0 In Skimage, CLAHE is perfored using *exposure.equalize_adapthist* For instance, in this example, http://scikit-image.org/docs/dev/auto_examples/plot_equalize.html *img_adapteq = exposure.equalize_adapthist(img, clip_limit=0.03)* My question is that how to setup the clip_limit value in skimage for a corresponding case in opencv For instance, in an example implemented using opencv, clipLimit is setup as 2.0; if I want to convert this implementation using skimage which value should I assign to clip_limit? According to the document looks like clip_limit between 0 and 1. *clip_limit : float, optional* *Clipping limit, normalized between 0 and 1 (higher values give more contrast).* while opencv does not have this limitation for clipLimit Thanks, Yuanyuan