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Hyperspectral image compression: adapting SPIHT and EZW to anisotropic 3-D wavelet coding.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2008
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Updated: Jul 14, 2026

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Joint source-channel coding using real BCH codes for robust image transmission.

Abraham Avi Gabay1, Michel Kieffer, Pierre Duhamel

  • 1The authors are with Laboratoire des Signaux et Systèmes, CNRS - Supélec- Univ Paris-Sud, 91192 Gif-sur-Yvette, France. avi_gabay@hotmail.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|June 6, 2007
PubMed
Summary

This study introduces a novel joint source-channel image coding scheme using real BCH codes. It offers improved robustness and performance over traditional tandem schemes, especially in challenging channel conditions like fading.

Related Experiment Videos

Last Updated: Jul 14, 2026

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Area of Science:

  • Digital Signal Processing
  • Information Theory
  • Image Compression

Background:

  • Standard image coding often uses tandem source and channel coding, introducing redundancy after source compression.
  • This approach can be suboptimal, particularly under varying or adverse channel conditions.
  • Robust transmission of still images requires efficient source-channel coding strategies.

Purpose of the Study:

  • To present a new still image coding scheme integrating source and channel coding.
  • To introduce redundancy before source coding using real BCH codes for enhanced robustness.
  • To evaluate the performance of the proposed joint coding scheme against standard tandem schemes.

Main Methods:

  • Development of a joint channel model representing a memoryless mixture of Gaussian and Bernoulli-Gaussian noise.
  • Derivation of decoding algorithms based on the joint channel model.
  • Comparison of the proposed joint coding scheme with state-of-the-art real BCH decoding and reference tandem coding schemes for still image transmission.

Main Results:

  • The joint coding scheme outperforms standard tandem schemes when the latter are not accurately tuned.
  • The proposed scheme demonstrates increased robustness compared to well-tuned tandem schemes as channel conditions degrade.
  • Soft performance degradation in the joint scheme allows for moderate image reconstruction even in deep fades.

Conclusions:

  • The proposed joint source-channel coding scheme offers superior robustness and performance for still image transmission.
  • Integrating redundancy before source coding with real BCH codes is an effective strategy for channel error resilience.
  • The scheme is particularly advantageous for fading channels due to its graceful performance degradation.