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Related Experiment Video

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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

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Published on: August 30, 2013

Operational rate-distortion performance for joint source and channel coding of images.

M J Ruf¹, J W Modestino

¹German Aerospace Research Establishment, Institute for Communications Technology, D-82234 Wessling, Germany.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|February 12, 2008

Summary

This study presents a method to optimize image transmission by balancing source coding accuracy and channel error protection. The approach achieves near-theoretical performance for combined source-channel coding over noisy channels.

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Area of Science:

Digital image processing
Information theory
Coding theory

Background:

Evaluating combined source and channel coding is crucial for efficient data transmission.
Optimizing the trade-off between compression and error correction is a key challenge.

Purpose of the Study:

To introduce a methodology for assessing the operational rate-distortion behavior of combined source-channel coding schemes for images.
To demonstrate the optimal trade-off between source coding accuracy and channel error protection within a fixed bandwidth.
To develop information-theoretic bounds and compare them with the proposed methodology's performance.

Main Methods:

Utilizing the operational rate-distortion function to analyze coding schemes.
Applying wavelet-based subband source coding.
Employing binary rate-compatible punctured convolutional (RCPC) codes for transmission.
Transmitting data over an additive white Gaussian noise (AWGN) channel.

Main Results:

The proposed methodology effectively determines the optimum trade-off for fixed bandwidth transmission.
Operational rate-distortion performance closely approaches developed information-theoretic bounds.
The combined source-channel coding approach demonstrates high efficacy for real-world image transmission.

Conclusions:

The developed methodology provides a robust framework for evaluating and optimizing combined source-channel coding for image transmission.
The approach achieves performance close to theoretical limits, showcasing its practical applicability.
Wavelet-based source coding and RCPC channel coding offer an effective solution for reliable image transmission over AWGN channels.