DocumentCode
1595845
Title
Slepian-Wolf Coding of Binary Finite Memory Source Using Burrows-Wheeler Transform
Author
Chen, Chao ; Ji, Xiangyang ; Dai, Qionghai ; Liu, Xiaodong
Author_Institution
Tsinghua Univ., Beijing
fYear
2009
Firstpage
440
Lastpage
440
Abstract
Summary form only given: In all existing codec designs for asymmetric Slepian-Wolf coding (SWC), it is assumed that the source sequence is i.i.d and equiprobable. When it comes to more complex source statistics, the encoder should firstly remove the redundancy within the source. However, this increases the complexity of the encoder. In this paper, we propose an asymmetric SWC scheme which explores the redundancy of the binary finite memory source (FMS) at the decoder. Specifically, inspired by the Burrows-Wheeler transform (BWT)-based source-controlled channel decoding algorithm proposed, we iteratively apply the LDPC decoding and BWT to the side information. In our codec implementation, the encoder is identical to the conventional LDPC-based SWC encoder. At the decoder, conventional LDPC-based SWC decoding algorithm and Burrows-Wheeler transform (BWT) are iteratively applied to the side information for decoding. BWT can asymptotically permute a FMS into a piece-wise i.i.d binary sequence. In other words, by applying BWT to the decoder side information, the redundancy in the memory is transformed into the redundancy in the marginal distributions of the output i.i.d segments. The marginal distributions of every i.i.d segment can be used as the a priori information for SWC decoding. To explore the marginal distribution, a segmentation algorithm is employed to adaptively partition the output sequence of BWT into i.i.d segments. The bias parameter of each segment is then empirically computed. Using these parameters, the a priori information of the FMS source can be derived and incorporated in the next iteration of SWC decoding. Experimental results show that our scheme performs significantly better than the scheme which does not utilize the a priori information for decoding.
Keywords
binary codes; combined source-channel coding; flowcharting; iterative decoding; parity check codes; Burrows-Wheeler transform; LDPC decoding; Slepian-Wolf coding; binary finite memory source; decoder; encoder complexity; flowchart; marginal distributions; source-controlled channel decoding algorithm; Binary sequences; Chaos; Codecs; Data compression; Flexible manufacturing systems; Flowcharts; Iterative algorithms; Iterative decoding; Parity check codes; Statistics; Burrows-Wheeler Transform; Distributed source coding; LDPC code; Slepian-Wolf coding;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Compression Conference, 2009. DCC '09.
Conference_Location
Snowbird, UT
ISSN
1068-0314
Print_ISBN
978-1-4244-3753-5
Type
conf
DOI
10.1109/DCC.2009.54
Filename
4976494
Link To Document