Gaussian Mixture Model Based Adaptive Gamma Correction
Anil Singh Parihar · 2017
In this paper an image contrast enhancement algorithm based adaptive gamma correction is presented. In traditional gamma correction method, using a single gamma value for entire image may result in unpleasant effects in images. In the proposed algorithm, an adaptive gamma is computed based on the Gaussian mixture model of the histogram of the given image. Thus, it incorporates the local characteristics of the image. The performance algorithm is investigated on large set of test images from standard data sets and compared with existing algorithms. Quantitative and visual analysis of resulting images show that the proposed algorithm is capable of enhancing contrast of the images without having noticeable undesirable effects. The algorithm performs comparatively with state-of-art algorithms.