File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Block-based compressive low-light-level imaging

TitleBlock-based compressive low-light-level imaging
Authors
Issue Date2013
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001148
Citation
The 2013 IEEE International Conference on Imaging Systems and Techniques (IST 2013), Beijing, China, 22-23 October 2013. In Conference Proceedings, 2013, p. 311-316 How to Cite?
AbstractIn 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. © 2013 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/201232
ISBN

 

DC FieldValueLanguage
dc.contributor.authorKe, Jen_US
dc.contributor.authorWei, Pen_US
dc.contributor.authorZhang, Xen_US
dc.contributor.authorLam, EYen_US
dc.date.accessioned2014-08-21T07:18:17Z-
dc.date.available2014-08-21T07:18:17Z-
dc.date.issued2013en_US
dc.identifier.citationThe 2013 IEEE International Conference on Imaging Systems and Techniques (IST 2013), Beijing, China, 22-23 October 2013. In Conference Proceedings, 2013, p. 311-316en_US
dc.identifier.isbn978-1-4673-5791-3-
dc.identifier.urihttp://hdl.handle.net/10722/201232-
dc.description.abstractIn 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. © 2013 IEEE.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001148-
dc.relation.ispartofIEEE International Workshop on Imaging Systems and Techniques Proceedingsen_US
dc.rightsIEEE International Workshop on Imaging Systems and Techniques. Copyright © IEEE.-
dc.rights©2013 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleBlock-based compressive low-light-level imagingen_US
dc.typeConference_Paperen_US
dc.identifier.emailKe, J: junke@eee.hku.hken_US
dc.identifier.emailLam, EY: elam@eee.hku.hken_US
dc.identifier.authorityLam, EY=rp00131en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/IST.2013.6729712-
dc.identifier.scopuseid_2-s2.0-84894476061-
dc.identifier.hkuros233716en_US
dc.identifier.spage311-
dc.identifier.epage316-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 140826-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats