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Transmission of Still Images Using Low-Complexity Analog Joint Source-Channel Coding
Jose Balsa1, Tomás Domínguez-Bolaño2, Óscar Fresnedo2
1Department of Computer Engineering, Universidade da Coruña (University of A Coruña), CITIC Research Center, Elviña, 15071 A Coruña, Spain. j.balsa@udc.es.
Sensors (Basel, Switzerland)
|July 7, 2019
Summary
A new analog joint source-channel coding (JSCC) system for still images offers performance comparable to digital JPEG methods. It provides better visual quality, lower complexity, and minimal delay, ideal for constrained applications.
Area of Science:
- Information Theory
- Digital Communications
- Image Processing
Background:
- Joint Source-Channel Coding (JSCC) is crucial for efficient data transmission.
- Digital image compression, like JPEG, faces limitations in low-power and real-time scenarios.
- Analog JSCC systems offer potential advantages in specific application contexts.
Purpose of the Study:
- To propose and evaluate an analog JSCC system for still image transmission.
- To compare its performance against digital JPEG and JPEG without entropy coding (JPEGw/oEC) alternatives.
- To assess its suitability for resource-constrained and real-time applications.
Main Methods:
- Development of an analog JSCC system for still images.
- Performance evaluation using Structural Similarity (SSIM) index and transmission time.
- Testing across Additive White Gaussian Noise (AWGN) and Rayleigh fading channels.
- Comparison with optimized digital schemes (JPEG and JPEGw/oEC).
Main Results:
- The analog JSCC system demonstrated performance similar to JPEG-based digital systems.
- The proposed analog system exhibited superior visual quality degradation.
- It achieved lower computational complexity and negligible transmission delay.
- Effectiveness was validated in AWGN and Rayleigh channel conditions.
Conclusions:
- Analog JSCC is a viable alternative for still image transmission under power and computational constraints.
- The system's efficiency and visual fidelity make it suitable for surveillance, IoT, and low-power devices.
- It offers a compelling solution for real-time image transmission applications.
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