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[1] Yin Weiwei, Mei Zhonghui, Wu Lenan,. Low complexity joint source-channel decoding for transmissionof wavelet compressed images [J]. Journal of Southeast University (English Edition), 2006, 22 (2): 148-152. [doi:10.3969/j.issn.1003-7985.2006.02.002]
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Low complexity joint source-channel decoding for transmissionof wavelet compressed images()
小波压缩图像传输的低复杂度信源-信道联合译码
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
22
Issue:
2006 2
Page:
148-152
Research Field:
Information and Communication Engineering
Publishing date:
2006-06-30

Info

Title:
Low complexity joint source-channel decoding for transmissionof wavelet compressed images
小波压缩图像传输的低复杂度信源-信道联合译码
Author(s):
Yin Weiwei Mei Zhonghui Wu Lenan
College of Information Science Engineering, Southeast University, Nanjing 210096, China
殷玮玮 梅中辉 吴乐南
东南大学信息科学与工程学院, 南京 210096
Keywords:
joint source-channel decoding sum-product algorithm generalized distribution law wavelet compressed image
信源-信道联合译码 和积算法 广义分配率 小波压缩图像
PACS:
TN91
DOI:
10.3969/j.issn.1003-7985.2006.02.002
Abstract:
To utilize residual redundancy to reduce the error induced by fading channels and decrease the complexity of the field model to describe the probability structure for residual redundancy, a simplified statistical model for residual redundancy and a low complexity joint source-channel decoding(JSCD)algorithm are proposed.The complicated residual redundancy in wavelet compressed images is decomposed into several independent 1-D probability check equations composed of Markov chains and it is regarded as a natural channel code with a structure similar to the low density parity check(LDPC)code.A parallel sum-product(SP)and iterative JSCD algorithm is proposed.Simulation results show that the proposed JSCD algorithm can make full use of residual redundancy in different directions to correct errors and improve the peak signal noise ratio(PSNR)of the reconstructed image and reduce the complexity and delay of JSCD.The performance of JSCD is more robust than the traditional separated encoding system with arithmetic coding in the same data rate.
为了利用小波压缩图像的残留冗余减小其经过衰落信道造成的传输错误, 并针对直接利用场模型描述残留冗余概率结构带来的较高计算复杂度, 提出了一种简化的残留冗余统计模型和低复杂度的信源-信道联合译码方法.小波压缩图像的复杂残留冗余统计模型被简化成多个独立的一维Markov链构成的统计校验方程, 并被看作是一种具有类似于LDPC码结构的天然信道编码, 在此基础上设计出一种并行的和积迭代联合译码算法.仿真显示该联合译码算法既可以充分利用多个方向的残留冗余进行纠错, 提高重建图像的PSNR, 又可以减小联合译码的复杂度和延时, 并且在同样的数据传输率下, 比利用算术码的传统分离编码系统鲁棒性更好.

References:

[1] Buch G, Burkert F, Hagenauer J, et al.To compress or not to compress [A].In:Proc of IEEE Communications Theory Miniconf [C].London, 1996.198-203.
[2] Fingscheidt T, Hindelang T, Cox R V, et al.Joint source-channel(de-)coding for mobile communications[J].IEEE Trans Commun, 2002, 50(2):200-212.
[3] Lahouti F, Khandani A K.Efficient source decoding over memoryless noisy channels using higher order Markov models [J].IEEE Transactions on Information Theory, 2004, 50(9):2103-2118.
[4] Park M, Miller D J.Improved image decoding over noisy channels using minimum mean-squared estimation and a Markov mesh [J].IEEE Transactions on Image Process, 1999, 8(6):863-867.
[5] Kschischang F R, Frey B J, Loeliger H A.Factor graphs and the sum-product algorithm [J].IEEE Transactions on Information Theory, 2001, 47(2):498-519.
[6] Kschischang F R, Frey B J.Iterative decoding of compound codes by probability propagation in graphical models [J].IEEE Journal on Selected Areas in Communications, 1998, 16(2):219-230.
[7] Aji S M, McEliece R J.The generalized distributive law [J]. IEEE Transactions on Information Theory, 2000, 46(2):325-343.
[8] Romberg J K, Hyeokho Choi, Baraniuk R G.Bayesian tree-structured image modeling using wavelet-domain hidden Markov models [J].IEEE Transactions on Image Process, 2001, 10(7):1056-1068.

Memo

Memo:
Biographies: Yin Weiwei(1978—), female, graduate;Wu Lenan(corresponding author), male, professor, wuln@seu.edu.cn.
Last Update: 2006-06-20