Quality Assessment of Contrast-Altered Images

In image / video systems, the contrast adjustment which manages to enhance the visual quality is nowadays an important research topic. Yet very limited efforts have been devoted to the exploration of image quality assessment (IQA) for contrast adjustment. To address the problem, this paper proposes a novel reduced-reference (RR) IQA metric with the integration of bottom-up and top-down strategies. The former one stems from the recently revealed free energy theory which tells that the human visual system always seeks to understand an input image by the uncertainty removal, while the latter one is towards using the symmetric K-L divergence to compare the histogram of the contrast-altered image with that of the reference image. The bottom-up and top-down strategies are lastly combined to derive the Reduced-reference Contrast-altered Image Quality Measure (RCIQM). A comparison with numerous existing IQA models is conducted on contrast related CID2013, CCID2014, CSIQ, TID2008 and TID2013 databases, and results validate the superiority of the proposed technique.