Compressive sensing for incoherent imaging systems with optical constraints

Francesco Renna; Miguel R.D. Rodrigues; Minhua Chen; Robert Calderbank; Lawrence Carin

doi:10.1109/ICASSP.2013.6638712

Compressive sensing for incoherent imaging systems with optical constraints

Francesco Renna, Miguel R.D. Rodrigues, Minhua Chen, Robert Calderbank, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

We consider the problem of linear projection design for incoherent optical imaging systems. We propose a computationally efficient method to obtain effective measurement kernels that satisfy the physical constraints imposed by an optical system, starting first from arbitrary kernels, including those that satisfy a less demanding power constraint. Performance is measured in terms of mutual information between the source input and the projection measurement, as well as reconstruction error for real world images. A clear improvement in the quality of image reconstructions is shown with respect to both random and adaptive projection designs in the literature. © 2013 IEEE.

Original language	English (US)
Title of host publication	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5484-5488
Number of pages	5
ISBN (Print)	9781479903566
DOIs	https://doi.org/10.1109/ICASSP.2013.6638712
State	Published - Oct 18 2013
Externally published	Yes

Access to Document

10.1109/ICASSP.2013.6638712

Cite this

@inproceedings{aea7ff419f7240b7af9e06b33d04af02,

title = "Compressive sensing for incoherent imaging systems with optical constraints",

abstract = "We consider the problem of linear projection design for incoherent optical imaging systems. We propose a computationally efficient method to obtain effective measurement kernels that satisfy the physical constraints imposed by an optical system, starting first from arbitrary kernels, including those that satisfy a less demanding power constraint. Performance is measured in terms of mutual information between the source input and the projection measurement, as well as reconstruction error for real world images. A clear improvement in the quality of image reconstructions is shown with respect to both random and adaptive projection designs in the literature. {\textcopyright} 2013 IEEE.",

author = "Francesco Renna and Rodrigues, {Miguel R.D.} and Minhua Chen and Robert Calderbank and Lawrence Carin",

note = "Generated from Scopus record by KAUST IRTS on 2021-02-09",

year = "2013",

month = oct,

day = "18",

doi = "10.1109/ICASSP.2013.6638712",

language = "English (US)",

isbn = "9781479903566",

pages = "5484--5488",

booktitle = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

}

Compressive sensing for incoherent imaging systems with optical constraints. / Renna, Francesco; Rodrigues, Miguel R.D.; Chen, Minhua et al.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2013. p. 5484-5488.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Compressive sensing for incoherent imaging systems with optical constraints

AU - Renna, Francesco

AU - Rodrigues, Miguel R.D.

AU - Chen, Minhua

AU - Calderbank, Robert

AU - Carin, Lawrence

N1 - Generated from Scopus record by KAUST IRTS on 2021-02-09

PY - 2013/10/18

Y1 - 2013/10/18

N2 - We consider the problem of linear projection design for incoherent optical imaging systems. We propose a computationally efficient method to obtain effective measurement kernels that satisfy the physical constraints imposed by an optical system, starting first from arbitrary kernels, including those that satisfy a less demanding power constraint. Performance is measured in terms of mutual information between the source input and the projection measurement, as well as reconstruction error for real world images. A clear improvement in the quality of image reconstructions is shown with respect to both random and adaptive projection designs in the literature. © 2013 IEEE.

AB - We consider the problem of linear projection design for incoherent optical imaging systems. We propose a computationally efficient method to obtain effective measurement kernels that satisfy the physical constraints imposed by an optical system, starting first from arbitrary kernels, including those that satisfy a less demanding power constraint. Performance is measured in terms of mutual information between the source input and the projection measurement, as well as reconstruction error for real world images. A clear improvement in the quality of image reconstructions is shown with respect to both random and adaptive projection designs in the literature. © 2013 IEEE.

UR - http://ieeexplore.ieee.org/document/6638712/

UR - http://www.scopus.com/inward/record.url?scp=84890472012&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2013.6638712

DO - 10.1109/ICASSP.2013.6638712

M3 - Conference contribution

SN - 9781479903566

SP - 5484

EP - 5488

BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Compressive sensing for incoherent imaging systems with optical constraints

Abstract

Access to Document

Other files and links

Fingerprint

Cite this