Contrast Enhancement Using Inverted Gaussian Histogram Specification Technique

Contrast enhancement has become a vital process in improving the human perception as well as machine perception, due to the enormous application of digital imaging techniques in various fields like medical, aerospace, agriculture, machine vision, automation, surveillance, etc. During contrast enhancement by various existing techniques, the advent of adverse side effects like brightness degradation, intensity saturation and appearance of artifacts in the enhanced images is a critical issue, which needs more research attention. In this paper, an inverted Gaussian histogram specification technique for contrast enhancement of differently skewed images is proposed, in which the pixel concentration on either side of the histogram is increased to overcome the drawbacks in the existing methods. The proposed technique uses parameters like mean, standard deviation and inversion constant to generate various inverted Gaussian specified histograms. Further, transformation and objective functions are used to identify the best desired histogram so as to obtain the best enhanced image for the given image. The performance of the proposed method is compared with other existing techniques on the images taken from various standard databases. The experimental results show that the proposed technique is best suitable for contrast enhancement of images with differently skewed histograms.