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Rate and power efficient image compressed sensing and transmission

[+] Author Affiliations
Saheed Olanigan, Lei Cao, Ramanarayanan Viswanathan

University of Mississippi, Department of Electrical Engineering, University, Mississippi 38677, United States

J. Electron. Imaging. 25(1), 013024 (Feb 04, 2016). doi:10.1117/1.JEI.25.1.013024
History: Received June 9, 2015; Accepted January 11, 2016
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Abstract.  This paper presents a suboptimal quantization and transmission scheme for multiscale block-based compressed sensing images over wireless channels. The proposed method includes two stages: dealing with quantization distortion and transmission errors. First, given the total transmission bit rate, the optimal number of quantization bits is assigned to the sensed measurements in different wavelet sub-bands so that the total quantization distortion is minimized. Second, given the total transmission power, the energy is allocated to different quantization bit layers based on their different error sensitivities. The method of Lagrange multipliers with Karush–Kuhn–Tucker conditions is used to solve both optimization problems, for which the first problem can be solved with relaxation and the second problem can be solved completely. The effectiveness of the scheme is illustrated through simulation results, which have shown up to 10 dB improvement over the method without the rate and power optimization in medium and low signal-to-noise ratio cases.

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Citation

Saheed Olanigan ; Lei Cao and Ramanarayanan Viswanathan
"Rate and power efficient image compressed sensing and transmission", J. Electron. Imaging. 25(1), 013024 (Feb 04, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.1.013024


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