Compressive Sensing Based Image Compression and Transmission for Noisy Channels

Yan Zhang

Prairie View A&M University, Prairie View, USA

Suxia Cui

Prairie View A&M University, Prairie View, USA

Yonghui Wang

Prairie View A&M University, Prairie View, USA

DOI: https://doi.org/10.20448/journal.526/2017.1.1/526.1.29.41

Keywords: Compressive sensing, Coding with feedback, Image transmission, Quantization, Joint source–channel coding.


Abstract

This paper presents the design of an optimized Compressive Sensing image compression technique for data transmission over noisy mobile wireless channel. The proposed technique is more robust to channel noise. It uses individual measurement driven coding scheme, which facilitates simpler encoder design. The shift of computational burden from encoder to decoder is more suitable for mobile devices applications where computational power and battery life are limited. This paper also presents a novel quantizer which allows the encoder to dynamically adapt to the channel conditions and provides optimum performance.

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