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Compressive Imaging using RIP-compliant CMOS Imager Architecture and Landweber Reconstruction

Trevisi, Marco, Akbari, Ali, Trocan, Maria, Rodriguez-Vazquez, Angel and Carmona-Galan, Ricardo (2019) Compressive Imaging using RIP-compliant CMOS Imager Architecture and Landweber Reconstruction IEEE Transactions on Circuits and Systems for Video Technology.

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Abstract

n this paper we present a new image sensor architecture for fast and accurate compressive sensing (CS) of natural images. Measurement matrices usually employed in compressive sensing CMOS image sensors (CS-CIS) are recursive pseudo-random binary matrices. We have proved that the restricted isometry property (RIP) of these matrices is limited by a low sparsity constant. The quality of these matrices is also affected by the non-idealities of pseudo-random numbers generators (PRNG). To overcome these limitations, we propose a hardware-friendly pseudo-random ternary measurement matrix generated on-chip by means of class III elementary cellular automata (ECA). These ECA present a chaotic behaviour that emulates random CS measurement matrices better than other PRNG. We have combined this new architecture with a block-based CS smoothed-projected Landweber (BCS-SPL) reconstruction algorithm. By means of single value decomposition (SVD) we have adapted this algorithm to perform fast and precise reconstruction while operating with binary and ternary matrices. Simulations are provided to qualify the approach

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
NameEmailORCID
Trevisi, Marco
Akbari, Aliali.akbari@surrey.ac.uk
Trocan, Maria
Rodriguez-Vazquez, Angel
Carmona-Galan, Ricardo
Date : 11 January 2019
DOI : 10.1109/TCSVT.2019.2892178
Additional Information : © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Maria Rodriguez-Marquez
Date Deposited : 23 Aug 2019 15:55
Last Modified : 23 Aug 2019 15:55
URI: http://epubs.surrey.ac.uk/id/eprint/852474

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