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Conference Paper: Modified CPI filter algorithm for removing salt-and-pepper noise in digital images

TitleModified CPI filter algorithm for removing salt-and-pepper noise in digital images
Authors
KeywordsPhysics
Optics
Instruments
Issue Date1996
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xml
Citation
Proceedings Of Spie - The International Society For Optical Engineering, 1996, v. 2727 n. 3/-, p. 1439-1449 How to Cite?
AbstractIn this paper, the theoretical aspects, implementation issues, and performance analysis of a modified CPI filter algorithm are presented. As the concept of the original CPI algorithm is to identify corrupted pixels by interrogating subimages, and considering the intensity spread of pixel values within the subimage when making a decision, the modified algorithm similarly takes into account the subimage gray level distribution across the whole gray scale. It works on the assumption that to consider which group in the subimage is corrupted, the multiple- feature histogram representing a subimage gray level distribution must be transformed into a two-feature histogram such that these two features can be mapped onto the two available pixel classes. This transformation is performed by using a 1-sigma decision about the mean intensity of the subimage, which enables pixels that fall inside the sigma bounds to be considered as uncorrupted, and the rest corrupted. A performance analysis of the modified CPI, original CPI, average, median and sigma algorithms is given for noisy images corrupted by salt-and- pepper noise of the impulsive and Gaussian nature, and gray noise over the signal-to-noise ratios (SNR) of plus 50 dB to minus 50 dB. The results show that similar to the original CPI algorithm, the modified CPI algorithm exhibits a number of desirable features. Firstly, due to its pixel identification property, it has better noise removing capability than the conventional filter algorithms. Secondly, most features in the original image are preserved in the restored image compared with, say, the median filter. Thirdly, iterative filtering of a noisy image using the CPI algorithm is possible.
Persistent Identifierhttp://hdl.handle.net/10722/45850
ISSN

 

DC FieldValueLanguage
dc.contributor.authorYung, Nelson Hen_HK
dc.contributor.authorLai, Hon Seng Aen_HK
dc.contributor.authorPoon, KMen_HK
dc.date.accessioned2007-10-30T06:36:54Z-
dc.date.available2007-10-30T06:36:54Z-
dc.date.issued1996en_HK
dc.identifier.citationProceedings Of Spie - The International Society For Optical Engineering, 1996, v. 2727 n. 3/-, p. 1439-1449en_HK
dc.identifier.issn0277-786Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/45850-
dc.description.abstractIn this paper, the theoretical aspects, implementation issues, and performance analysis of a modified CPI filter algorithm are presented. As the concept of the original CPI algorithm is to identify corrupted pixels by interrogating subimages, and considering the intensity spread of pixel values within the subimage when making a decision, the modified algorithm similarly takes into account the subimage gray level distribution across the whole gray scale. It works on the assumption that to consider which group in the subimage is corrupted, the multiple- feature histogram representing a subimage gray level distribution must be transformed into a two-feature histogram such that these two features can be mapped onto the two available pixel classes. This transformation is performed by using a 1-sigma decision about the mean intensity of the subimage, which enables pixels that fall inside the sigma bounds to be considered as uncorrupted, and the rest corrupted. A performance analysis of the modified CPI, original CPI, average, median and sigma algorithms is given for noisy images corrupted by salt-and- pepper noise of the impulsive and Gaussian nature, and gray noise over the signal-to-noise ratios (SNR) of plus 50 dB to minus 50 dB. The results show that similar to the original CPI algorithm, the modified CPI algorithm exhibits a number of desirable features. Firstly, due to its pixel identification property, it has better noise removing capability than the conventional filter algorithms. Secondly, most features in the original image are preserved in the restored image compared with, say, the median filter. Thirdly, iterative filtering of a noisy image using the CPI algorithm is possible.en_HK
dc.format.extent741204 bytes-
dc.format.extent2251 bytes-
dc.format.extent10863 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xmlen_HK
dc.relation.ispartofProceedings of SPIE - The International Society for Optical Engineeringen_HK
dc.rightsS P I E - the International Society for Optical Proceedings. Copyright © S P I E - International Society for Optical Engineering.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsCopyright 1996 Society of Photo-Optical Instrumentation Engineers. This paper was published in Visual Communications and Image Processing, Orlando, Florida, USA, 17-20 March 1996, v. 2727, p. 1439-1449 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.en_HK
dc.subjectPhysicsen_HK
dc.subjectOpticsen_HK
dc.subjectInstrumentsen_HK
dc.titleModified CPI filter algorithm for removing salt-and-pepper noise in digital imagesen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0277-786X&volume=2727&spage=1439&epage=1449&date=1996&atitle=Modified+CPI+filter+algorithm+for+removing+salt-and-pepper+noise+in+digital+imagesen_HK
dc.identifier.emailYung, Nelson H:nyung@eee.hku.hken_HK
dc.identifier.authorityYung, Nelson H=rp00226en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1117/12.233219en_HK
dc.identifier.scopuseid_2-s2.0-0030405051en_HK
dc.identifier.hkuros11675-
dc.identifier.volume2727en_HK
dc.identifier.issue3/-en_HK
dc.identifier.spage1439en_HK
dc.identifier.epage1449en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYung, Nelson H=7003473369en_HK
dc.identifier.scopusauthoridLai, Hon Seng A=7201967327en_HK
dc.identifier.scopusauthoridPoon, KM=7006268762en_HK

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