Histogram processing – histogram equalization and matching

Histogram processing techniques provide a better method for altering the dynamic range of pixel values in an image so that its intensity histogram has a desired shape. As we have seen, image enhancement by the contrast stretching operation is limited in the sense that it can apply only linear scaling functions.

 

 

Histogram processing techniques can be more powerful by employing non-linear (and non-monotonic) transfer functions to map the input pixel intensities to the output pixel intensities. In this section, we shall demonstrate the implementation of a couple of such techniques, namely histogram equalization and histogram matching, using the scikit-image library's exposure module.

Contrast stretching and histogram equalization with scikit-image

Histogram equalization uses a monotonic and a non-linear mapping which reassigns the pixel intensity values in the input image in such a way that the output image has a uniform distribution...