Title :
Joint Source-Channel Coding Using Real BCH Codes for Robust Image Transmission
Author :
Gabay, A. ; Kieffer, M. ; Duhamel, P.
Author_Institution :
Lab. des Signaux et Systemes, Univ. Paris-Sud, Gif-sur-Yvette
fDate :
6/1/2007 12:00:00 AM
Abstract :
In this paper, a new still image coding scheme is presented. In contrast with standard tandem coding schemes, where the redundancy is introduced after source coding, it is introduced before source coding using real BCH codes. A joint channel model is first presented. The model corresponds to a memoryless mixture of Gaussian and Bernoulli-Gaussian noise. It may represent the source coder, the channel coder, the physical channel, and their corresponding decoder. Decoding algorithms are derived from this channel model and compared to a state-of-art real BCH decoding scheme. A further comparison with two reference tandem coding schemes and the proposed joint coding scheme for the robust transmission of still images has been presented. When the tandem scheme is not accurately tuned, the joint coding scheme outperforms the tandem scheme in all situations. Compared to a tandem scheme well tuned for a given channel situation, the joint coding scheme shows an increased robustness as the channel conditions worsen. The soft performance degradation observed when the channel worsens gives an additional advantage to the joint source-channel coding scheme for fading channels, since a reconstruction with moderate quality may be still possible, even if the channel is in a deep fade
Keywords :
BCH codes; Gaussian noise; combined source-channel coding; decoding; fading channels; image coding; image reconstruction; visual communication; BCH decoding scheme; Bernoulli-Gaussian noise; channel coder; decoding algorithms; fading channels; joint source-channel coding; real BCH codes; robust image transmission; source coder; standard tandem coding schemes; still image coding scheme; Code standards; Decoding; Degradation; Fading; Gaussian noise; Image coding; Image communication; Image reconstruction; Robustness; Source coding; Channel coding; Gaussian–Bernoulli–Gaussian (GBG) channel model; impulse noise; joint source-channel coding (JSCC); source coding; Algorithms; Computer Communication Networks; Computer Simulation; Data Compression; Image Enhancement; Image Interpretation, Computer-Assisted; Models, Statistical; Numerical Analysis, Computer-Assisted; Signal Processing, Computer-Assisted;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2007.896698