File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Blind bi-level image restoration with iterated quadratic programming

TitleBlind bi-level image restoration with iterated quadratic programming
Authors
KeywordsBi-level images
Blind deconvolution
Image restoration
Iteration
Resolution enhancement
Issue Date2007
PublisherIEEE.
Citation
IEEE Transactions On Circuits And Systems II: Express Briefs, 2007, v. 54 n. 1, p. 52-56 How to Cite?
AbstractMany camera systems are dedicated to the capture of bi-level objects, including documents, bar codes, handwritten signatures, and vehicle license plates. Degradations in the imaging systems, however, cause blurring to the output images and introduce many more intensity levels. The blurring often arises from the optical aberrations and motions between the object and the camera, and hampers any computer vision algorithms aimed at automatic recognition and identification of these images. While image restoration has been applied frequently in such cases, many of these algorithms do not explicitly incorporate knowledge of a bi-level object, but attempt to apply a generic restoration scheme followed by thresholding. Such two-step algorithms may not produce the best results. On the other hand, directly restoring a bi-level object is a combinatorial task and is therefore time-consuming. In this brief, we propose a method that treats the blind restoration method as an iterated quadratic programming optimization problem. This has the properties of fast convergence and good numerical stability, due to established schemes such as the interior-point algorithm. The output of our algorithm is very nearly binary. Simulation results show that by integrating the computation in the imaging system, this proposed technique can restore weak signals that would have been lost with a simple thresholding. © 2007 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/44766
ISSN
2006 Impact Factor: 0.922
2007 SCImago Journal Rankings: 1.092
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLam, EYen_HK
dc.date.accessioned2007-10-30T06:09:46Z-
dc.date.available2007-10-30T06:09:46Z-
dc.date.issued2007en_HK
dc.identifier.citationIEEE Transactions On Circuits And Systems II: Express Briefs, 2007, v. 54 n. 1, p. 52-56en_HK
dc.identifier.issn1057-7130en_HK
dc.identifier.urihttp://hdl.handle.net/10722/44766-
dc.description.abstractMany camera systems are dedicated to the capture of bi-level objects, including documents, bar codes, handwritten signatures, and vehicle license plates. Degradations in the imaging systems, however, cause blurring to the output images and introduce many more intensity levels. The blurring often arises from the optical aberrations and motions between the object and the camera, and hampers any computer vision algorithms aimed at automatic recognition and identification of these images. While image restoration has been applied frequently in such cases, many of these algorithms do not explicitly incorporate knowledge of a bi-level object, but attempt to apply a generic restoration scheme followed by thresholding. Such two-step algorithms may not produce the best results. On the other hand, directly restoring a bi-level object is a combinatorial task and is therefore time-consuming. In this brief, we propose a method that treats the blind restoration method as an iterated quadratic programming optimization problem. This has the properties of fast convergence and good numerical stability, due to established schemes such as the interior-point algorithm. The output of our algorithm is very nearly binary. Simulation results show that by integrating the computation in the imaging system, this proposed technique can restore weak signals that would have been lost with a simple thresholding. © 2007 IEEE.en_HK
dc.format.extent676911 bytes-
dc.format.extent4084 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE Transactions on Circuits and Systems II: Express Briefsen_HK
dc.rights©2007 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.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBi-level imagesen_HK
dc.subjectBlind deconvolutionen_HK
dc.subjectImage restorationen_HK
dc.subjectIterationen_HK
dc.subjectResolution enhancementen_HK
dc.titleBlind bi-level image restoration with iterated quadratic programmingen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1549-7747&volume=54&issue=1&spage=52&epage=56&date=2007&atitle=Blind+Bi-Level+Image+Restoration+With+Iterated+Quadratic+Programmingen_HK
dc.identifier.emailLam, EY:elam@eee.hku.hken_HK
dc.identifier.authorityLam, EY=rp00131en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TCSII.2006.883101en_HK
dc.identifier.scopuseid_2-s2.0-33847681386en_HK
dc.identifier.hkuros125262-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33847681386&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume54en_HK
dc.identifier.issue1en_HK
dc.identifier.spage52en_HK
dc.identifier.epage56en_HK
dc.identifier.isiWOS:000243890700012-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLam, EY=7102890004en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats