An Effective Gaussian Fitting Approach for Image Contrast Enhancement

Abstract

Contrast enhancement plays an important role in image processing applications. This paper proposes a low-complexity automatic method for contrast enhancement. The method exploits the high-frequency distribution of an image to estimate an intensity-weighting matrix, which is then used to control the Gaussian fitting curve and shape the distribution of the contrast gain. As such, the curve can be easily designed to enhance the important details hidden in noteworthy regions. Subsequently, the proposed grayscale transformation that is obtained from the Gaussian fitting can rationally express contrast distribution. Unlike previous contrast enhancement methods, our technique is fully automatic and target-oriented in the sense that it can be directly applied to any input image without any parameter adjustment. The experimental results for some of the widely accepted criterions demonstrate the superiority of our proposed method over the conventional enhancement techniques, especially in the aspects of visual pleasure, anti-noise capability, and target-oriented contrast enhancement.