Paper Info
Title
A Contourlet-Based Embedded Image Coding Scheme on Low Bit-Rate
Abstract
Contourlet transform (CT) is a new image representation method, which can efficiently represent contours and textures in images. However, CT is a kind of overcomplete transform with a redundancy factor of 4/3. If it is applied to image compression straightforwardly, the encoding bit-rate may increase to meet a given distortion. This fact baffles the coding community to develop CT-based image compression techniques with satisfactory performance. In this paper, we analyze the distribution of significant contourlet coefficients in different subbands and propose a new contourlet-based embedded image coding (CEIC) scheme on low bit-rate. The well-known wavelet-based embedded image coding (WEIC) algorithms such as EZW, SPIHT and SPECK can be easily integrated into the proposed scheme by constructing a virtual low frequency subband, modifying the coding framework of WEIC algorithms according to the structure of contourlet coefficients, and adopting a high-efficiency significant coefficient scanning scheme for CEIC scheme. The proposed CEIC scheme can provide an embedded bit-stream, which is desirable in heterogeneous networks. Our experiments demonstrate that the proposed scheme can achieve the better compression performance on low bit-rate. Furthermore, thanks to the contourlet adopted in the proposed scheme, more contours and textures in the coded images are preserved to ensure the superior subjective quality.
Year
DOI
Venue
2008
10.1093/ietisy/e91-d.9.2333
IEICE Transactions
Keywords
Field
DocType
ceic scheme,new contourlet-based embedded image,new image representation method,image compression straightforwardly,low bit-rate,proposed scheme,coding community,well-known wavelet-based embedded image,ct-based image compression technique,proposed ceic scheme,heterogeneous network,image compression,contourlet,low frequency,wavelet
Computer vision,Pattern recognition,Set partitioning in hierarchical trees,Computer science,Image processing,Redundancy (engineering),Artificial intelligence,Data compression,Distortion,Contourlet,Image compression,Wavelet
Journal
Volume
Issue
ISSN
E91-D
9
1745-1361
Citations 
PageRank 
References 
2
0.40
8
Authors
2
Name
Order
Citations
PageRank
Haohao Song1262.35
Yu Song235652.74