On iterative source-channel image decoding with Markov random field source models

Jörg Kliewer; Norbert Görtz; Alfred Mertins

doi:10.1109/ICASSP.2004.1326913

On iterative source-channel image decoding with Markov random field source models

Jörg Kliewer, Norbert Görtz, Alfred Mertins

Institute of Signal Processing

Abstract

In this paper we propose a novel iterative source-channel decoding approach for robust transmission of compressed still images over noisy communication channels. Besides the explicit redundancy introduced by channel encoding also implicit residual source redundancy is exploited for error protection. The source redundancy is modeled by a Markov random field (MRF) source model, which considers the residual spatial correlation after source encoding. The resulting MRF-based soft-input/soft-output source decoder is used as outer constituent decoder in the proposed iterative source-channel decoding scheme, where due to the link between MRFs and the Gibbs distribution, the source decoder can be implemented with very low complexity, We show that this iterative decoding scheme can be successfully employed for recovering the image data, especially when the channel is highly corrupted.

Original language	English
Title of host publication	2004 IEEE International Conference on Acoustics, Speech, and Signal Processing
Number of pages	4
Volume	4
Publisher	IEEE
Publication date	27.09.2004
Pages	661-664
ISBN (Print)	0-7803-8484-9
DOIs	https://doi.org/10.1109/ICASSP.2004.1326913
Publication status	Published - 27.09.2004
Event	Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing 2004 - Montreal, Canada Duration: 17.05.2004 → 21.05.2004 Conference number: 63500

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Kliewer, J., Görtz, N., & Mertins, A. (2004). On iterative source-channel image decoding with Markov random field source models. In 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing (Vol. 4, pp. 661-664). (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 4). IEEE. https://doi.org/10.1109/ICASSP.2004.1326913

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title = "On iterative source-channel image decoding with Markov random field source models",

abstract = "In this paper we propose a novel iterative source-channel decoding approach for robust transmission of compressed still images over noisy communication channels. Besides the explicit redundancy introduced by channel encoding also implicit residual source redundancy is exploited for error protection. The source redundancy is modeled by a Markov random field (MRF) source model, which considers the residual spatial correlation after source encoding. The resulting MRF-based soft-input/soft-output source decoder is used as outer constituent decoder in the proposed iterative source-channel decoding scheme, where due to the link between MRFs and the Gibbs distribution, the source decoder can be implemented with very low complexity, We show that this iterative decoding scheme can be successfully employed for recovering the image data, especially when the channel is highly corrupted.",

author = "J{\"o}rg Kliewer and Norbert G{\"o}rtz and Alfred Mertins",

year = "2004",

month = sep,

day = "27",

doi = "10.1109/ICASSP.2004.1326913",

language = "English",

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series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

publisher = "IEEE",

pages = "661--664",

booktitle = "2004 IEEE International Conference on Acoustics, Speech, and Signal Processing",

note = "Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing 2004 ; Conference date: 17-05-2004 Through 21-05-2004",

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Kliewer, J, Görtz, N & Mertins, A 2004, On iterative source-channel image decoding with Markov random field source models. in 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing. vol. 4, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 4, IEEE, pp. 661-664, Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing 2004 , Montreal, Quebec, Canada, 17.05.04. https://doi.org/10.1109/ICASSP.2004.1326913

On iterative source-channel image decoding with Markov random field source models. / Kliewer, Jörg; Görtz, Norbert; Mertins, Alfred.
2004 IEEE International Conference on Acoustics, Speech, and Signal Processing. Vol. 4 IEEE, 2004. p. 661-664 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 4).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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AU - Görtz, Norbert

AU - Mertins, Alfred

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Y1 - 2004/9/27

N2 - In this paper we propose a novel iterative source-channel decoding approach for robust transmission of compressed still images over noisy communication channels. Besides the explicit redundancy introduced by channel encoding also implicit residual source redundancy is exploited for error protection. The source redundancy is modeled by a Markov random field (MRF) source model, which considers the residual spatial correlation after source encoding. The resulting MRF-based soft-input/soft-output source decoder is used as outer constituent decoder in the proposed iterative source-channel decoding scheme, where due to the link between MRFs and the Gibbs distribution, the source decoder can be implemented with very low complexity, We show that this iterative decoding scheme can be successfully employed for recovering the image data, especially when the channel is highly corrupted.

AB - In this paper we propose a novel iterative source-channel decoding approach for robust transmission of compressed still images over noisy communication channels. Besides the explicit redundancy introduced by channel encoding also implicit residual source redundancy is exploited for error protection. The source redundancy is modeled by a Markov random field (MRF) source model, which considers the residual spatial correlation after source encoding. The resulting MRF-based soft-input/soft-output source decoder is used as outer constituent decoder in the proposed iterative source-channel decoding scheme, where due to the link between MRFs and the Gibbs distribution, the source decoder can be implemented with very low complexity, We show that this iterative decoding scheme can be successfully employed for recovering the image data, especially when the channel is highly corrupted.

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DO - 10.1109/ICASSP.2004.1326913

M3 - Conference contribution

SN - 0-7803-8484-9

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T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

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BT - 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing

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T2 - Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing 2004

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ER -

On iterative source-channel image decoding with Markov random field source models

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