Contextual and Variational Contrast Enhancement

This paper proposes an algorithm that enhances the contrast of an input image using interpixel contextual information. The algorithm uses a 2-D histogram of the input image constructed using a mutual relationship between each pixel and its neighboring pixels. A smooth 2-D target histogram is obtained by minimizing the sum of Frobenius norms of the differences from the input histogram and the uniformly distributed histogram. The enhancement is achieved by mapping the diagonal elements of the input histogram to the diagonal elements of the target histogram. Experimental results show that the algorithm produces better or comparable enhanced images than four state-of-the-art algorithms.

I. Introduction

Contrast enhancement is used to either increase the contrast of an image with low dynamic range or to bring out image details that would be otherwise hidden [1]. The enhanced image subjectively looks better than the original image as the gray-level differences (i.e., the contrast) among objects and background are increased.