Visual quality metric for perceptual video coding
The visual quality assessment (VQA) becomes prevailing in the studies of image and video coding. It assesses the quality of image or video more accurately than mean square error (MSE) with respect to the human visual system (HVS). Toward perceptual video coding, MSE is weighted spatially and temporally to simulate the HVS response to visual signal in this paper. Firstly, the image content is depicted by edge strength to compose spatial weighting factors. Secondly, the motion strength calculated from motion vector of each block gives temporal weighting factors. Thirdly, the motion trajectory based saliency map for video signal is integrated as another weighting factor of MSE. The proposed VQM not only efficiently model HVS but also relate to quantization parameter (QP) capable of guiding perceptual video coding. A perceptual rate distortion optimization (RDO) is established on the proposed VQM. The experimental results indicate that the proposed VQM is consistent well with HVS. In addition, the better rate-distortion efficiency and accurate bit rate control can be achieved by the proposed visual quality control algorithm.