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Article: Performance evaluation of a feature-preserving filtering algorithm for removing additive random noise in digital images

TitlePerformance evaluation of a feature-preserving filtering algorithm for removing additive random noise in digital images
Authors
KeywordsCorrupted-pixel identification
Feature preserving filtering
Gaussian white noise
Impulse noise
Mean-square error
Noise removal
Issue Date1996
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oe
Citation
Optical Engineering, 1996, v. 35 n. 7, p. 1871-1885 How to Cite?
AbstractWe evaluate the performance of a feature-preserving filtering algorithm over a range of images corrupted by typical additive random noise against three common spatial filter algorithms: median, sigma and averaging. The concept of the new algorithm is based on a corrupted-pixel identification methodology over a variable subimage size. Rather than processing every pixel indiscriminately in a digital image, this corrupted-pixel identification algorithm interrogates the image in variable-sized subimage regions to determine which are the corrupted pixels and which are not. As a result, only the corrupted pixels are being filtered, whereas the uncorrupted pixels are untouched. Extensive evaluation of the algorithm over a large number of noisy images shows that the corrupted-pixel identification algorithm exhibits three major characteristics. First, its ability in removing additive random noise is better visually (subjective) and has the smallest mean-square errors (objective) in all cases compared with the median filter, averaging filter and sigma filter. Second, the effect of smoothing introduced by the new filter is minimal. In other words, most edge and line sharpness is preserved. Third, the corrupted-pixel identification algorithm is consistently faster than the median and sigma filters in all our test cases. © 1996 Society of Photo-Optical Instrumentation Engineers.
Persistent Identifierhttp://hdl.handle.net/10722/44730
ISSN
2015 Impact Factor: 0.984
2015 SCImago Journal Rankings: 0.485
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYung, NHCen_HK
dc.contributor.authorLai, AHSen_HK
dc.date.accessioned2007-10-30T06:08:57Z-
dc.date.available2007-10-30T06:08:57Z-
dc.date.issued1996en_HK
dc.identifier.citationOptical Engineering, 1996, v. 35 n. 7, p. 1871-1885en_HK
dc.identifier.issn0091-3286en_HK
dc.identifier.urihttp://hdl.handle.net/10722/44730-
dc.description.abstractWe evaluate the performance of a feature-preserving filtering algorithm over a range of images corrupted by typical additive random noise against three common spatial filter algorithms: median, sigma and averaging. The concept of the new algorithm is based on a corrupted-pixel identification methodology over a variable subimage size. Rather than processing every pixel indiscriminately in a digital image, this corrupted-pixel identification algorithm interrogates the image in variable-sized subimage regions to determine which are the corrupted pixels and which are not. As a result, only the corrupted pixels are being filtered, whereas the uncorrupted pixels are untouched. Extensive evaluation of the algorithm over a large number of noisy images shows that the corrupted-pixel identification algorithm exhibits three major characteristics. First, its ability in removing additive random noise is better visually (subjective) and has the smallest mean-square errors (objective) in all cases compared with the median filter, averaging filter and sigma filter. Second, the effect of smoothing introduced by the new filter is minimal. In other words, most edge and line sharpness is preserved. Third, the corrupted-pixel identification algorithm is consistently faster than the median and sigma filters in all our test cases. © 1996 Society of Photo-Optical Instrumentation Engineers.en_HK
dc.format.extent1890599 bytes-
dc.format.extent10863 bytes-
dc.format.mimetypeapplication/pdf-
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://www.spie.org/oeen_HK
dc.relation.ispartofOptical Engineeringen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsOptical Engineering. Copyright © S P I E - International Society for Optical Engineering.en_HK
dc.rightsCopyright 1996 Society of Photo-Optical Instrumentation Engineers. This paper was published in Optical Engineering, 1996, v. 35 n. 7, p. 1871-1885 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.subjectCorrupted-pixel identificationen_HK
dc.subjectFeature preserving filteringen_HK
dc.subjectGaussian white noiseen_HK
dc.subjectImpulse noiseen_HK
dc.subjectMean-square erroren_HK
dc.subjectNoise removalen_HK
dc.titlePerformance evaluation of a feature-preserving filtering algorithm for removing additive random noise in digital imagesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0091-3286&volume=35&issue=7&spage=1871&epage=1885&date=1996&atitle=Performance+evaluation+of+a+feature-preserving+filtering+algorithm+for+removing+additive+random+noise+in+digital+imagesen_HK
dc.identifier.emailYung, NHC:nyung@eee.hku.hken_HK
dc.identifier.authorityYung, NHC=rp00226en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1117/1.600769en_HK
dc.identifier.scopuseid_2-s2.0-0042098373en_HK
dc.identifier.hkuros11672-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0042098373&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume35en_HK
dc.identifier.issue7en_HK
dc.identifier.spage1871en_HK
dc.identifier.epage1885en_HK
dc.identifier.isiWOS:A1996VA11600010-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK
dc.identifier.scopusauthoridLai, AHS=7102225794en_HK

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