Principle of Maximum Entropy for Histogram Transformation and Image Enhancement

In this paper, we present a histogram transformation technique which can be used for image enhancement in 2D images. It is based on the application of the Principle of Maximum Entropy (PME) for histogram modification. Firstly, a PME problem is proposed in the context of the nonextensive entropy and its implicit solution is presented. Then, an iterative scheme is used to get the solution with a desired precision. Finally, we perform a transformation in the intensity values of the input image which attempts to alter its spatial histogram to match the PME distribution. In the case study we take some examples in order to demonstrate the advantages of the technique as a preprocessing step in an image segmentation pipeline.