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.