Information optimal scalable compressive imager demonstrator

Ronan Kerviche, Nan Zhu, Amit Ashok

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We present a compressive imager demonstrator based on a scalable, parallel architecture. It primarily utilizes information-optimal projections and a Piece-wise Linear Minimum Mean Square Error Estimator (PLE-MMSE) combined with a block-based statistical model of natural images. Such system delivers high-resolution images from low resolution sensor with near real-time snapshots. This testbed provides a highly programmable compressive imager that allows testing of a variety of projection designs for different tasks (e.g. random binary, PCA) and also enables adaptive or dynamic designs.

Original languageEnglish (US)
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2177-2179
Number of pages3
ISBN (Print)9781479957514
DOIs
StatePublished - Jan 28 2014

Fingerprint

Image sensors
Parallel architectures
Optical resolving power
Image resolution
Testbeds
Mean square error
Sensors
Testing
Statistical Models

Keywords

  • Compressed Imaging
  • Mutual Information
  • PLE-MMSE

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Kerviche, R., Zhu, N., & Ashok, A. (2014). Information optimal scalable compressive imager demonstrator. In 2014 IEEE International Conference on Image Processing, ICIP 2014 (pp. 2177-2179). [7025439] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIP.2014.7025439

Information optimal scalable compressive imager demonstrator. / Kerviche, Ronan; Zhu, Nan; Ashok, Amit.

2014 IEEE International Conference on Image Processing, ICIP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2177-2179 7025439.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kerviche, R, Zhu, N & Ashok, A 2014, Information optimal scalable compressive imager demonstrator. in 2014 IEEE International Conference on Image Processing, ICIP 2014., 7025439, Institute of Electrical and Electronics Engineers Inc., pp. 2177-2179. https://doi.org/10.1109/ICIP.2014.7025439
Kerviche R, Zhu N, Ashok A. Information optimal scalable compressive imager demonstrator. In 2014 IEEE International Conference on Image Processing, ICIP 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 2177-2179. 7025439 https://doi.org/10.1109/ICIP.2014.7025439
Kerviche, Ronan ; Zhu, Nan ; Ashok, Amit. / Information optimal scalable compressive imager demonstrator. 2014 IEEE International Conference on Image Processing, ICIP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 2177-2179
@inproceedings{f5cceb5b150849098bafb92ac8a459fb,
title = "Information optimal scalable compressive imager demonstrator",
abstract = "We present a compressive imager demonstrator based on a scalable, parallel architecture. It primarily utilizes information-optimal projections and a Piece-wise Linear Minimum Mean Square Error Estimator (PLE-MMSE) combined with a block-based statistical model of natural images. Such system delivers high-resolution images from low resolution sensor with near real-time snapshots. This testbed provides a highly programmable compressive imager that allows testing of a variety of projection designs for different tasks (e.g. random binary, PCA) and also enables adaptive or dynamic designs.",
keywords = "Compressed Imaging, Mutual Information, PLE-MMSE",
author = "Ronan Kerviche and Nan Zhu and Amit Ashok",
year = "2014",
month = "1",
day = "28",
doi = "10.1109/ICIP.2014.7025439",
language = "English (US)",
isbn = "9781479957514",
pages = "2177--2179",
booktitle = "2014 IEEE International Conference on Image Processing, ICIP 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Information optimal scalable compressive imager demonstrator

AU - Kerviche, Ronan

AU - Zhu, Nan

AU - Ashok, Amit

PY - 2014/1/28

Y1 - 2014/1/28

N2 - We present a compressive imager demonstrator based on a scalable, parallel architecture. It primarily utilizes information-optimal projections and a Piece-wise Linear Minimum Mean Square Error Estimator (PLE-MMSE) combined with a block-based statistical model of natural images. Such system delivers high-resolution images from low resolution sensor with near real-time snapshots. This testbed provides a highly programmable compressive imager that allows testing of a variety of projection designs for different tasks (e.g. random binary, PCA) and also enables adaptive or dynamic designs.

AB - We present a compressive imager demonstrator based on a scalable, parallel architecture. It primarily utilizes information-optimal projections and a Piece-wise Linear Minimum Mean Square Error Estimator (PLE-MMSE) combined with a block-based statistical model of natural images. Such system delivers high-resolution images from low resolution sensor with near real-time snapshots. This testbed provides a highly programmable compressive imager that allows testing of a variety of projection designs for different tasks (e.g. random binary, PCA) and also enables adaptive or dynamic designs.

KW - Compressed Imaging

KW - Mutual Information

KW - PLE-MMSE

UR - http://www.scopus.com/inward/record.url?scp=84949928263&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84949928263&partnerID=8YFLogxK

U2 - 10.1109/ICIP.2014.7025439

DO - 10.1109/ICIP.2014.7025439

M3 - Conference contribution

AN - SCOPUS:84949928263

SN - 9781479957514

SP - 2177

EP - 2179

BT - 2014 IEEE International Conference on Image Processing, ICIP 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -