Improved sub-band JND model with textural decomposition and its application in perceptual image coding - Ming-kui ZHENG; Kai-xiong SU; Wei-xing WANG; Cheng-dong LAN; Xiu-zhi YANG (Tongxin xuebao)
In order to improve the accuracy of the just noticeable difference (JND) model in transform domain, an en-hanced JND model with a new method for contrast masking factor estimation was proposed. The image was decomposed and the textural image was used for an accurate block classification, thus the accurate JND in DCT domain was obtained. The improved JND model was applied on the perceptual image coding. Considering the compatibility and the auxiliary information which would affect the encoding efficiency, the JND model was adjusted to the quantization process and re-moved more visual redundancy. Experimental results show that the proposed algorithm can improve the JND threshold;compared with JPEG standard, the perceptual coding method can save more bit rate and does not need extra bit for auxil-iary information at the similar visual quality. The proposed algorithm is also applicable to the perceptual video coding.