Contextual Information Based Quality Assessment for Contrast-Changed Images

Abstract

In this letter, we propose the objective metric that can precisely predict the perceptual quality of contrast-changed images using inter-pixel contextual information. The metric consists of two parts. One is a two-dimensional (2-D) histogram-based contrast quality measure that utilizes the distribution of the gray-level differences between adjacent pixels. We design the desired 2-D histogram considering the characteristic of an adequately high contrast image and predict contrast quality by comparing the desired 2-D histogram with 2-D histograms of an original image and a contrast-changed image. The other is a spatial entropy based one that uses the information of spatial location distribution of gray-levels. A comparison is carried out with many IQA metrics on five contrast related databases. Experimental results show that the proposed metric provides a more accurate prediction of human perception of contrast change than other metrics.