Visual masking estimation based on structural uncertainty

Jinjian Wu, Weisi Lin, Guangming Shi

Abstract: A model of visual masking, which reveals the visible threshold of human perception, is useful in perceptual based image/video processing. The existing visual masking formulation, which mainly considers luminance contrast, cannot accurately estimate the visible threshold. Recent researches indicate that human perception is highly adaptive to extract orderly structures and is insensitive to disorderly structures. Therefore, we suggest that the structural characteristic is another determining factor for visual masking, and deduce a novel visual masking function based on structural uncertainty. Experimental results demonstrate that the proposed model is more consistent with human perception than the existing visual masking model.