Perceptually-Friendly H.264/AVC Video Coding Based on Foveated Just-Noticeable-Distortion Model

Abstract

Traditional video compression methods remove spatial and temporal redundancy based on the signal statistical correlation. However, to reach higher compression ratios without perceptually degrading the reconstructed signal, the properties of the human visual system (HVS) need to be better exploited. Research effort has been dedicated to modeling the spatial and temporal just-noticeable-distortion (JND) based on the sensitivity of the HVS to luminance contrast, and accounting for spatial and temporal masking effects. This paper describes a foveation model as well as a foveated JND (FJND) model in which the spatial and temporal JND models are enhanced to account for the relationship between visibility and eccentricity. Since the visual acuity decreases when the distance from the fovea increases, the visibility threshold increases with increased eccentricity. The proposed FJND model is then used for macroblock (MB) quantization adjustment in H.264/advanced video coding (AVC). For each MB, the quantization parameter is optimized based on its FJND information. The Lagrange multiplier in the rate-distortion optimization is adapted so that the MB noticeable distortion is minimized. The performance of the FJND model has been assessed with various comparisons and subjective visual tests. It has been shown that the proposed FJND model can increase the visual quality versus rate performance of the H.264/AVC video coding scheme.