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Related Concept Videos

Encoding01:19

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Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
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Arithmetic Sequences01:30

Arithmetic Sequences

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Related Experiment Video

Updated: Jul 14, 2026

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
06:49

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Published on: June 16, 2014

Iterative decoding of serially concatenated arithmetic and channel codes with JPEG 2000 applications.

Marco Grangetto1, Bartolo Scanavino, Gabriella Olmo

  • 1Center for Multimedia Radio Communica- qans (CERCOM), Department of Electronics, Politecnico di Torino, 10129 Torino, Italy. marco.grangetto@polito.it

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 coding scheme for improved data transmission. It enables iterative soft decoding of arithmetic codes, enhancing performance over AWGN channels and demonstrating practical application in JPEG 2000 image compression.

Related Experiment Videos

Last Updated: Jul 14, 2026

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
06:49

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Published on: June 16, 2014

Area of Science:

  • Information Theory
  • Digital Communications
  • Image Processing

Background:

  • Traditional separated source and channel coding can be suboptimal.
  • Arithmetic codes offer high compression efficiency but are sensitive to channel errors.
  • Iterative decoding techniques can improve error resilience.

Purpose of the Study:

  • To develop and evaluate an innovative joint-source channel coding (JSCC) scheme.
  • To enable iterative soft decoding of arithmetic codes for enhanced performance.
  • To demonstrate the practical application of the JSCC scheme in JPEG 2000 image compression.

Main Methods:

  • A joint-source channel coding scheme utilizing an error-resilient arithmetic coder with a forbidden symbol.
  • A soft-in/soft-out decoder employing suboptimal search and pruning of a binary tree for iterative decoding.
  • Performance evaluation across Additive White Gaussian Noise (AWGN) channels in terms of word error probability.
  • Investigation of interleaver gain, system convergence, and optimal source/channel rate allocation.

Main Results:

  • The proposed JSCC scheme outperforms traditional separated approaches in terms of word error probability.
  • The system exhibits good convergence properties and demonstrates significant interleaver gain.
  • Optimal source and channel rate allocation strategies are investigated for performance optimization.
  • The JSCC approach shows practical relevance when integrated with JPEG 2000 for image transmission.

Conclusions:

  • The developed JSCC scheme provides a robust and efficient method for data transmission, particularly for image compression standards like JPEG 2000.
  • Iterative soft decoding of arithmetic codes significantly enhances error resilience and overall system performance.
  • The joint decoding approach offers a practical advantage over separated coding schemes in noisy channel environments.