A Perceptual Weighted Trellis-Coded Quantization Algorithm

The rate-distortion optimization algorithm (RDOTCQ) was proposed to improve the coding performance efficiently in our former work. However, human visual characteristics are not considered. In this paper, a perceptual weighted rate-distortion optimization TCQ (PRDOTCQ) algorithm is proposed. By introducing the vision model that takes into account various masking effects of human visual perception and a perceptual distortion metric, the proposed algorithm obtains better subjective quality. The experiment shows that PRDOTCQ algorithm provides better performance compared to SPIHT with the maximum gain 0.6dB. Though it behaves a little PSNR loss compared with RDOTCQ, it results in better subjective quality with the same rate.

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