Application of JND visual model to SPHIT image coding and performance evaluation

The wavelet based SPIHT algorithm has recently attracted significant attention from researchers in image coding. SPIHT maximizes PSNR (or minimize MSE) for each bit transmitted. However, it is well known that PSNR is not a good indicator of the perceptual image fidelity. Human visual perception is more sensitive to distortions in the lower frequency components than distortions in the higher frequency components. In this paper, we enhance SPIHT by introducing a process called JND-SQ, between wavelet transform and SPIHT. JND-SQ allows SPIHT to maximize perceptual fidelity instead of PSNR for each bit transmitted. We proposed a perceptual fidelity criterion called JND-PSNR based on the SY JND model, the new criterion is more consistent with human perception than PSNR. Experimental results show that JND SPIHT outperforms SPIHT in terms of JND PSNR. The JND-SQ process results in a large amount of zeros, which can be further utilized to improve the speed of SPIHT. Finally, JND-SQ can be turned off if the original SPIHT is desired.