Arithmetic coding for data compression
Communications of the ACM
Joint Source/Channel Coding for Variable Length Codes
DCC '98 Proceedings of the Conference on Data Compression
Reversible Variable Length Codes for Efficient and Robust Image and Video Coding
DCC '98 Proceedings of the Conference on Data Compression
Image Transmission Using Arithmetic Coding Based Continuous Error Detection
DCC '98 Proceedings of the Conference on Data Compression
Joint Source Channel Coding Using Arithmetic Codes and Trellis Coded Modulation
DCC '01 Proceedings of the Data Compression Conference
Source coding algorithms for fast data compression.
Source coding algorithms for fast data compression.
A new error resilience technique for image compression using arithmetic coding
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
Arithmetic coding-based continuous error detection for efficient ARQ-based image transmission
IEEE Journal on Selected Areas in Communications
Joint source-channel turbo decoding of entropy-coded sources
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Image Processing
Joint source-channel decoding of variable-length codes with soft information: a survey
EURASIP Journal on Applied Signal Processing
Error recovery properties and soft decoding of quasi-arithmetic codes
EURASIP Journal on Advances in Signal Processing
Computation of posterior marginals on aggregated state models for soft source decoding
IEEE Transactions on Communications
IEEE Transactions on Communications
Distributed coding using punctured quasi-arithmetic codes for memory and memoryless sources
IEEE Transactions on Signal Processing
Distributed coding using punctured quasi-arithmetic codes for memory and memoryless sources
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
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The issue of robust and joint source-channel decoding of quasi-arithmetic codes is addressed. Quasi-arithmetic coding is a reduced precision and complexity implementation of arithmetic coding. This amounts to approximating the distribution of the source. The approximation of the source distribution leads to the introduction of redundancy that can be exploited for robust decoding in presence of transmission errors. Hence, this approximation controls both the trade-off between compression efficiency and complexity and at the same time the redundancy (excess rate) introduced by this suboptimality. This paper provides first a state model of a quasi-arithmetic coder and decoder for binary and M-ary sources. The design of an error-resilient soft decoding algorithm follows quite naturally. The compression efficiency of quasi-arithmetic codes allows to add extra redundancy in the form of markers designed specifically to prevent desynchronization. The algorithm is directly amenable for iterative source-channel decoding in the spirit of serial turbo codes. The coding and decoding algorithms have been tested for a wide range of channel signal-to-noise ratios (SNRs). Experimental results reveal improved symbol error rate (SER) and SNR performances against Huffman and optimal arithmetic codes.