Issues in vision modeling for perceptual video quality assessment
Signal Processing
A distortion measure for blocking artifacts in images based on human visual sensitivity
IEEE Transactions on Image Processing
A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile
IEEE Transactions on Circuits and Systems for Video Technology
Motion-compensated residue preprocessing in video coding based on just-noticeable-distortion profile
IEEE Transactions on Circuits and Systems for Video Technology
Perceivable artifacts in compressed video and their relation to video quality
Image Communication
A vision modeling framework for DHM using geometrically estimated FoV
Computer-Aided Design
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A novel approach towards a simplified, though still reliable human vision model based on the spatial masking properties of the human visual system (HVS) is presented. The model contains two basic characteristics of the HVS, namely texture masking and luminance masking. These masking effects are implemented as simple spatial filtering followed by a weighting function, and are efficiently combined into a single visibility coefficient. This HVS model is applied to a blockiness metric by using its output to scale the blockedge strength. To validate the proposed model, its performance in the blockiness metric is determined by comparing it to the same blockiness metric having different HVS-based models embedded. The results show that the proposed model is indeed simple, without compromising its accuracy.