Multiple description coding based on enhanced X-tree

Abstract

This paper proposes a multiple description image coding scheme based on 2D dual-tree transform and the enhanced x-tree encoding method. The input image is firstly mapped into 2D dual-tree discrete wavelet domain to form 2 wavelet coefficient trees. A sparse algorithm is then used to remove the most redundant wavelet coefficients resulted from dual-tree discrete wavelet transform (DDWT), forming the basic component of both descriptions, respectively. In order to improve the quality of the side reconstruction, a side sparse algorithm is then imposed on two sparse coefficient trees to produce the additional for both side decoding. The basic information from one tree and additional information from the other are sent to an enhanced x-tree encoder, which is proposed to exploit the strong correlation between two wavelet trees resulted from DDWT, forming the bitstream of a description. Since each description includes the basic information and part of details of the input image, even one of the descriptions gets lost, the reconstructed image can still keep acceptable quality. Simulation results have verified that the proposed algorithm has good coding performance and error resilient ability.