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Article: A mathematical analysis of the DCT coefficient distributions for images

TitleA mathematical analysis of the DCT coefficient distributions for images
Authors
KeywordsDiscrete Cosine Transforms
Gaussian Distributions
Image Analysis
Image Coding
Probability Statistics
Issue Date2000
Citation
Ieee Transactions On Image Processing, 2000, v. 9 n. 10, p. 1661-1666 How to Cite?
AbstractOver the past two decades, there have been various studies on the distributions of the DCT coefficients for images. However, they have concentrated only on fitting the empirical data from some standard pictures with a variety of well-known statistical distributions, and then comparing their goodness-of-fit. The Laplacian distribution is the dominant choice balancing simplicity of the model and fidelity to the empirical data. Yet, to the best of our knowledge, there has been no mathematical justification as to what gives rise to this distribution. In this paper, we offer a rigorous mathematical analysis using a doubly stochastic model of the images, which not only provides the theoretical explanations necessary, but also leads to insights about various other observations from the literature. This model also allows us to investigate how certain changes in the image statistics could affect the DCT coefficient distributions. © 2000 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/155135
ISSN
2023 Impact Factor: 10.8
2023 SCImago Journal Rankings: 3.556
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLam, EYen_US
dc.contributor.authorGoodman, JWen_US
dc.date.accessioned2012-08-08T08:32:00Z-
dc.date.available2012-08-08T08:32:00Z-
dc.date.issued2000en_US
dc.identifier.citationIeee Transactions On Image Processing, 2000, v. 9 n. 10, p. 1661-1666en_US
dc.identifier.issn1057-7149en_US
dc.identifier.urihttp://hdl.handle.net/10722/155135-
dc.description.abstractOver the past two decades, there have been various studies on the distributions of the DCT coefficients for images. However, they have concentrated only on fitting the empirical data from some standard pictures with a variety of well-known statistical distributions, and then comparing their goodness-of-fit. The Laplacian distribution is the dominant choice balancing simplicity of the model and fidelity to the empirical data. Yet, to the best of our knowledge, there has been no mathematical justification as to what gives rise to this distribution. In this paper, we offer a rigorous mathematical analysis using a doubly stochastic model of the images, which not only provides the theoretical explanations necessary, but also leads to insights about various other observations from the literature. This model also allows us to investigate how certain changes in the image statistics could affect the DCT coefficient distributions. © 2000 IEEE.en_US
dc.languageengen_US
dc.relation.ispartofIEEE Transactions on Image Processingen_US
dc.subjectDiscrete Cosine Transformsen_US
dc.subjectGaussian Distributionsen_US
dc.subjectImage Analysisen_US
dc.subjectImage Codingen_US
dc.subjectProbability Statisticsen_US
dc.titleA mathematical analysis of the DCT coefficient distributions for imagesen_US
dc.typeArticleen_US
dc.identifier.emailLam, EY:elam@eee.hku.hken_US
dc.identifier.authorityLam, EY=rp00131en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/83.869177en_US
dc.identifier.scopuseid_2-s2.0-0034298708en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0034298708&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume9en_US
dc.identifier.issue10en_US
dc.identifier.spage1661en_US
dc.identifier.epage1666en_US
dc.identifier.isiWOS:000089483200002-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridLam, EY=7102890004en_US
dc.identifier.scopusauthoridGoodman, JW=7402288924en_US
dc.identifier.issnl1057-7149-

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