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Journal of Electronic Imaging

Rate and power efficient image compressed sensing and transmission
Author(s): Saheed Olanigan; Lei Cao; Ramanarayanan Viswanathan
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Paper 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.

Paper Details

Date Published: 4 February 2016
PDF: 8 pages
J. Electron. Imaging. 25(1) 013024 doi: 10.1117/1.JEI.25.1.013024
Published in: Journal of Electronic Imaging Volume 25, Issue 1
Show Author Affiliations
Saheed Olanigan, Univ. of Mississippi (United States)
Lei Cao, Univ. of Mississippi (United States)
Ramanarayanan Viswanathan, Univ. of Mississippi (United States)

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