Abstract
Contourlet is a new image representation method, which can efficiently represent contours and textures in images. In this paper, we analyze the distribution of significant contourlet coefficients in different subbands and propose a contourlet image coding algorithm by constructing a virtual low frequency subband and adjusting coding method of SPIHT (Set Partitioning in Hierarchical Trees) algorithm according to the structure of contourlet coefficients. The proposed coding algorithm can provide an embedded bit stream, which is very desirable in heterogeneous networks. Our experiments demonstrate that the proposed coding algorithm can achieve better or competitive compression performance when compared with traditional wavelet transform with SPIHT and wavelet-based contourlet transform with SPIHT, which both are embedded image coding algorithms based on two non-redundant transforms. At the same time, benefiting from genuine contourlet adopted in the proposed coding algorithm, more contours and textures in the coded images are preserved to ensure superior subjective quality.
Li Song
Professor, IEEE Senior Member
Professor, Doctoral Supervisor, the Deputy Director of the Institute of Image Communication and Network Engineering of Shanghai Jiao Tong University, the Double-Appointed Professor of the Institute of Artificial Intelligence and the Collaborative Innovation Center of Future Media Network, the Deputy Secretary-General of the China Video User Experience Alliance and head of the standards group.