Soft decoding and synchronization of arithmetic codes: application to image transmission over noisy channels

This paper addresses the issue of robust and joint source-channel decoding of arithmetic codes. We first analyze dependencies between the variables involved in arithmetic coding by means of the Bayesian formalism. This provides a suitable framework for designing a soft decoding algorithm that provides high error-resilience. It also provides a natural setting for "soft synchronization", i.e., to introduce anchors favoring the likelihood of "synchronized" paths. In order to maintain the complexity of the estimation within a realistic range, a simple, yet efficient, pruning method is described. The algorithm can be placed in an iterative source-channel decoding structure, in the spirit of serial turbo codes. Models and algorithms are then applied to context-based arithmetic coding widely used in practical systems (e.g., JPEG-2000). Experimentation results with both theoretical sources and with real images coded with JPEG-2000 reveal very good error resilience performances.

[1]  Jeffrey Scott Vitter,et al.  Analysis of arithmetic coding for data compression , 1991, [1991] Proceedings. Data Compression Conference.

[2]  Jorma Rissanen,et al.  Generalized Kraft Inequality and Arithmetic Coding , 1976, IBM J. Res. Dev..

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

[4]  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).

[5]  David J. Miller,et al.  A sequence-based approximate MMSE decoder for source coding over noisy channels using discrete hidden Markov models , 1998, IEEE Trans. Commun..

[6]  Michael W. Marcellin,et al.  An overview of JPEG-2000 , 2000, Proceedings DCC 2000. Data Compression Conference.

[7]  George F. Elmasry.  Joint lossless-source and channel coding using automatic repeat request , 1999, IEEE Trans. Commun..

[8]  J. Chou,et al.  Arithmetic coding-based continuous error detection for efficient ARQ-based image transmission , 2000, IEEE Journal on Selected Areas in Communications.

[9]  A. R. Reibman,et al.  Self-synchronizing variable-length codes for image transmission , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[10]  Ian H. Witten,et al.  Text Compression , 1990, 125 Problems in Text Algorithms.

[11]  Joachim Hagenauer,et al.  Iterative source/channel decoding based on a trellis representation for variable length codes , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).

[12]  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).

[13]  Ian H. Witten,et al.  Arithmetic coding revisited , 1998, TOIS.

[14]  Kannan Ramchandran,et al.  Image transmission using arithmetic coding based continuous error detection , 1998, Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225).

[15]  John D. Villasenor,et al.  Reversible variable length codes for efficient and robust image and video coding , 1998, Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225).

[16]  Khalid Sayood,et al.  Joint source channel coding using arithmetic codes and trellis coded modulation , 2001, Proceedings DCC 2001. Data Compression Conference.

[17]  M. Wada,et al.  Reversible variable length codes , 1995, IEEE Trans. Commun..

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

[19]  K. P. Subbalakshmi,et al.  On the joint source-channel decoding of variable-length encoded sources: the BSC case , 2001, IEEE Trans. Commun..

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

[21]  Richard Clark Pasco,et al.  Source coding algorithms for fast data compression , 1976 .

[22]  Khalid Sayood,et al.  Joint source/channel coding for variable length codes , 2000, IEEE Trans. Commun..

[23]  David S. Taubman,et al.  High performance scalable image compression with EBCOT , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[24]  Christine Guillemot,et al.  Joint source-channel turbo decoding of entropy-coded sources , 2001, IEEE J. Sel. Areas Commun..

[25]  G. F. Elmasry.  Embedding channel coding in arithmetic coding , 1999 .

[26]  Thomas E. Fuja,et al.  Joint source-channel decoding of variable-length encoded sources , 1998, 1998 Information Theory Workshop (Cat. No.98EX131).

[27]  Jeffrey Scott Vitter,et al.  Arithmetic coding for data compression , 1994 .

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

[29]  Thomas J. Ferguson,et al.  Self-synchronizing Huffman codes , 1984, IEEE Trans. Inf. Theory.