Chase-Like Decoding of Arithmetic Codes with Applications

Motivated by recent results in Joint Source/ Channel JSC coding and decoding, this paper addresses the problem of soft input decoding of Arithmetic Codes AC. A new length-constrained scheme for JSC decoding of these codes is proposed based on the Maximum a posteriori MAP sequence estimation criterion. The new decoder, called Chase-like arithmetic decoder is supposed to know the source symbol sequence and the compressed bit-stream lengths. First, Packet Error Rates PER in the case of transmission on an Additive White Gaussian Noise AWGN channel are investigated. Compared to classical arithmetic decoding, the Chase-like decoder shows significant improvements. Results are provided for Chase-like decoding for image compression and transmission on an AWGN channel. Both lossy and lossless image compression schemes were studied. As a final application, the serial concatenation of an AC with a convolutional code was considered. Iterative decoding, performed between the two decoders showed substantial performance improvement through iterations.

[1]  Irene Yu-Hua Gu,et al.  Joint Space-Time-Range Mean ShiftBased Image and Video Segmentation , 2006 .

[2]  Iraj Sodagar,et al.  A new error resilience technique for image compression using arithmetic coding , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[3]  Ammar Bouallègue,et al.  Low-Complexity Joint Source/Channel Turbo Decoding of Arithmetic Codes with Image Transmission Application , 2009, 2009 Data Compression Conference.

[4]  Joachim Hagenauer,et al.  A Viterbi algorithm with soft-decision outputs and its applications , 1989, IEEE Global Telecommunications Conference, 1989, and Exhibition. 'Communications Technology for the 1990s and Beyond.

[5]  Gabriella Olmo,et al.  Iterative Decoding of Serially Concatenated Arithmetic and Channel Codes With JPEG 2000 Applications , 2007, IEEE Transactions on Image Processing.

[6]  John G. Cleary,et al.  Integrating error detection into arithmetic coding , 1997, IEEE Trans. Commun..

[7]  Yun Q. Shi,et al.  MAP symbol decoding of arithmetic coding with embedded channel coding , 1999, WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466).

[8]  Ian H. Witten,et al.  Arithmetic coding for data compression , 1987, CACM.

[9]  R. Pyndiah,et al.  Low-complexity joint source/channel turbo decoding of arithmetic codes , 2008, 2008 5th International Symposium on Turbo Codes and Related Topics.

[10]  Glen G. Langdon,et al.  Arithmetic Coding , 1979 .

[11]  Nick G. Kingsbury,et al.  The EREC: an error-resilient technique for coding variable-length blocks of data , 1996, IEEE Trans. Image Process..

[12]  Jossy Sayir.  Arithmetic coding for noisy channels , 1999, Proceedings of the 1999 IEEE Information Theory and Communications Workshop (Cat. No. 99EX253).

[13]  Thomas Guionnet,et al.  Soft decoding and synchronization of arithmetic codes: application to image transmission over noisy channels , 2003, IEEE Trans. Image Process..

[14]  Ramesh Pyndiah,et al.  Near-optimum decoding of product codes: block turbo codes , 1998, IEEE Trans. Commun..

[15]  David Chase,et al.  Class of algorithms for decoding block codes with channel measurement information , 1972, IEEE Trans. Inf. Theory.

[16]  Kannan Ramchandran,et al.  Continuous error detection (CED) for reliable communication , 2001, IEEE Trans. Commun..

[17]  Khalid Sayood,et al.  Joint source/channel coding using arithmetic codes , 2001, IEEE Trans. Commun..

[18]  Mohamed Fakir,et al.  Recognition of Color Objects Using Hybrids Descriptors , 2013, Int. J. Comput. Vis. Image Process..

[19]  G. Olmo,et al.  Joint source/channel coding and MAP decoding of arithmetic codes , 2005, IEEE Transactions on Communications.

[20]  M. Kieffer,et al.  Analytical tools for optimizing the error correction performance of arithmetic codes , 2008, IEEE Transactions on Communications.

[21]  John Cocke,et al.  Optimal decoding of linear codes for minimizing symbol error rate (Corresp.) , 1974, IEEE Trans. Inf. Theory.

[22]  Jian Cheng,et al.  Computer Vision for Multimedia Applications: Methods and Solutions , 2010 .

[23]  Yu-Jin Zhang,et al.  Advances in image and video segmentation , 2006 .

[24]  Kannan Ramchandran,et al.  Arithmetic coding based continuous error detection for efficient ARQ-based image transmission , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[25]  Khalid Sayood,et al.  State machine interpretation of arithmetic codes for joint source and channel coding , 2006, Data Compression Conference (DCC'06).

[26]  William A. Pearlman,et al.  A new, fast, and efficient image codec based on set partitioning in hierarchical trees , 1996, IEEE Trans. Circuits Syst. Video Technol..

[27]  Glen G. Langdon,et al.  An Introduction to Arithmetic Coding , 1984, IBM J. Res. Dev..