In this section, we are going to see how to apply contrast limited adaptive histogram equalization (CLAHE) to equalize images, which is a variant of adaptive histogram equalization (AHE), in which contrast amplification is limited. The noise in relatively homogeneous regions of the image is overamplified by AHE, while CLAHE tackles this problem by limiting the contrast amplification. This algorithm can be applied to improve the contrast of images. This algorithm works by creating several histograms of the original image, and uses all of these histograms to redistribute the lightness of the image.
In the clahe_histogram_equalization.py script, we are applying CLAHE to both grayscale and color images. When applying CLAHE, there are two parameters to tune. The first one is clipLimit, which sets the threshold for contrast limiting...
