Block-based compressive low-light-level imaging

Jun Ke; Ping Wei; Xin Zhang; Edmund Y. Lam

doi:10.1109/IST.2013.6729712

Block-based compressive low-light-level imaging

Jun Ke, Ping Wei, Xin Zhang, Edmund Y. Lam

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

5 Citations (Scopus)

Abstract

In this paper, block-based compressive low-light-level imaging (BCL-imaging) is studied. To obtain larger measurement SNR (signal to noise ratio), instead of object pixels, linear combinations of pixels, referred to as features, are collected. PCA and Hadamard features are studied. Measurement SNR and reconstruction error are analyzed to quantify BCL-imaging performance. Compared with conventional imaging, BCL-imaging presents better reconstruction quality. Between PCA and Hadamard projections, PCA has smaller reconstruction error. However, after sorting the projection vectors using measurement SNR, Hadamard can obtain similarly performance as PCA. Biased vector and dual-measurements are studied with experimental results for the implementation of both projections in the end of this paper.

Original language	English
Title of host publication	IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings
Pages	311-316
Number of pages	6
DOIs	https://doi.org/10.1109/IST.2013.6729712
Publication status	Published - 2013
Externally published	Yes
Event	2013 IEEE International Conference on Imaging Systems and Techniques, IST 2013 - Beijing, China Duration: 22 Oct 2013 → 23 Oct 2013

Publication series

Name	IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings

Conference

Conference	2013 IEEE International Conference on Imaging Systems and Techniques, IST 2013
Country/Territory	China
City	Beijing
Period	22/10/13 → 23/10/13

Access to Document

10.1109/IST.2013.6729712

Cite this

Ke, J., Wei, P., Zhang, X., & Lam, E. Y. (2013). Block-based compressive low-light-level imaging. In IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings (pp. 311-316). Article 6729712 (IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings). https://doi.org/10.1109/IST.2013.6729712

@inproceedings{12186f4de2714d65b7855bec1bcdfd6e,

title = "Block-based compressive low-light-level imaging",

abstract = "In this paper, block-based compressive low-light-level imaging (BCL-imaging) is studied. To obtain larger measurement SNR (signal to noise ratio), instead of object pixels, linear combinations of pixels, referred to as features, are collected. PCA and Hadamard features are studied. Measurement SNR and reconstruction error are analyzed to quantify BCL-imaging performance. Compared with conventional imaging, BCL-imaging presents better reconstruction quality. Between PCA and Hadamard projections, PCA has smaller reconstruction error. However, after sorting the projection vectors using measurement SNR, Hadamard can obtain similarly performance as PCA. Biased vector and dual-measurements are studied with experimental results for the implementation of both projections in the end of this paper.",

author = "Jun Ke and Ping Wei and Xin Zhang and Lam, {Edmund Y.}",

year = "2013",

doi = "10.1109/IST.2013.6729712",

language = "English",

isbn = "9781467357906",

series = "IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings",

pages = "311--316",

booktitle = "IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings",

note = "2013 IEEE International Conference on Imaging Systems and Techniques, IST 2013 ; Conference date: 22-10-2013 Through 23-10-2013",

}

Ke, J, Wei, P, Zhang, X & Lam, EY 2013, Block-based compressive low-light-level imaging. in IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings., 6729712, IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings, pp. 311-316, 2013 IEEE International Conference on Imaging Systems and Techniques, IST 2013, Beijing, China, 22/10/13. https://doi.org/10.1109/IST.2013.6729712

Block-based compressive low-light-level imaging. / Ke, Jun; Wei, Ping; Zhang, Xin et al.
IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings. 2013. p. 311-316 6729712 (IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings).

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

TY - GEN

T1 - Block-based compressive low-light-level imaging

AU - Ke, Jun

AU - Wei, Ping

AU - Zhang, Xin

AU - Lam, Edmund Y.

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N2 - In this paper, block-based compressive low-light-level imaging (BCL-imaging) is studied. To obtain larger measurement SNR (signal to noise ratio), instead of object pixels, linear combinations of pixels, referred to as features, are collected. PCA and Hadamard features are studied. Measurement SNR and reconstruction error are analyzed to quantify BCL-imaging performance. Compared with conventional imaging, BCL-imaging presents better reconstruction quality. Between PCA and Hadamard projections, PCA has smaller reconstruction error. However, after sorting the projection vectors using measurement SNR, Hadamard can obtain similarly performance as PCA. Biased vector and dual-measurements are studied with experimental results for the implementation of both projections in the end of this paper.

AB - In this paper, block-based compressive low-light-level imaging (BCL-imaging) is studied. To obtain larger measurement SNR (signal to noise ratio), instead of object pixels, linear combinations of pixels, referred to as features, are collected. PCA and Hadamard features are studied. Measurement SNR and reconstruction error are analyzed to quantify BCL-imaging performance. Compared with conventional imaging, BCL-imaging presents better reconstruction quality. Between PCA and Hadamard projections, PCA has smaller reconstruction error. However, after sorting the projection vectors using measurement SNR, Hadamard can obtain similarly performance as PCA. Biased vector and dual-measurements are studied with experimental results for the implementation of both projections in the end of this paper.

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U2 - 10.1109/IST.2013.6729712

DO - 10.1109/IST.2013.6729712

M3 - Conference contribution

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SN - 9781467357906

T3 - IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings

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EP - 316

BT - IST 2013 - 2013 IEEE International Conference on Imaging Systems and Techniques, Proceedings

T2 - 2013 IEEE International Conference on Imaging Systems and Techniques, IST 2013

Y2 - 22 October 2013 through 23 October 2013

ER -

Block-based compressive low-light-level imaging

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