Adaptive Distributed Source Coding

We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion...

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Veröffentlicht in:IEEE transactions on image processing Jg. 21; H. 5; S. 2630 - 2640
Hauptverfasser: Varodayan, D., Yao-Chung Lin, Girod, B.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.05.2012
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Applied sciences
Approximation
Codes
Coding
Coding, codes
Complexity theory
Data Compression - methods
Decoders
Decoding
Density
Detection, estimation, filtering, equalization, prediction
Doping
Entropy
Exact sciences and technology
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Information, signal and communications theory
Mathematical models
Monitoring
Monitoring systems
Parity check codes
Photography - methods
Reproducibility of Results
Sensitivity and Specificity
Signal and communications theory
Signal processing
Signal Processing, Computer-Assisted
Signal, noise
Source coding
Studies
sum product algorithm
Telecommunications and information theory
Vectors
Video Recording - methods
video signal processing
Performance evaluation
Source coding
Coding circuit
Doping
Distributed source signal
Information rate
Video technique
Decoding
Algorithm
Information transmission
Video signal processing
Remote sensing
Adaptive coding
Image quality
Monitoring system
Quality control
sum product algorithm
Remote supervision
ISSN:1057-7149, 1941-0042, 1941-0042
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Beschreibung
Zusammenfassung:We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.
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ISSN:1057-7149
1941-0042
1941-0042
DOI:10.1109/TIP.2011.2175936