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Article: An improved embedded zerotree wavelet image coding method based on coefficient partitioning using morphological operation

TitleAn improved embedded zerotree wavelet image coding method based on coefficient partitioning using morphological operation
Authors
Issue Date2000
PublisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijprai/ijprai.shtml
Citation
International Journal Of Pattern Recognition And Artificial Intelligence, 2000, v. 14 n. 6, p. 795-807 How to Cite?
AbstractIn recent years, wavelets have attracted great attention in both still image compression and video coding, and several novel wavelet-based image compression algorithms have been developed so far, one of which is Shapiro's embedded zerotree wavelet (EZW) image compression algorithm. However, there are still some deficiencies in this algorithm. In this paper, after the analysis of the deficiency in EZW, a new algorithm based on quantized coefficient partitioning using morphological operation is proposed. Instead of encoding the coefficients in each subband line-by-line, regions in which most of the quantized coefficients are significant are extracted by morphological dilation and encoded first. This is followed by using zerotrees to encode the remaining space which has mostly zeros. Experimental results show that the proposed algorithm is not only superior to the EZW, but also compares favorably with the most efficient wavelet-based image compression algorithms reported so far.
Persistent Identifierhttp://hdl.handle.net/10722/155132
ISSN
2023 Impact Factor: 0.9
2023 SCImago Journal Rankings: 0.302
References

 

DC FieldValueLanguage
dc.contributor.authorZhong, Jen_US
dc.contributor.authorLeung, CHen_US
dc.contributor.authorTang, YYen_US
dc.date.accessioned2012-08-08T08:32:00Z-
dc.date.available2012-08-08T08:32:00Z-
dc.date.issued2000en_US
dc.identifier.citationInternational Journal Of Pattern Recognition And Artificial Intelligence, 2000, v. 14 n. 6, p. 795-807en_US
dc.identifier.issn0218-0014en_US
dc.identifier.urihttp://hdl.handle.net/10722/155132-
dc.description.abstractIn recent years, wavelets have attracted great attention in both still image compression and video coding, and several novel wavelet-based image compression algorithms have been developed so far, one of which is Shapiro's embedded zerotree wavelet (EZW) image compression algorithm. However, there are still some deficiencies in this algorithm. In this paper, after the analysis of the deficiency in EZW, a new algorithm based on quantized coefficient partitioning using morphological operation is proposed. Instead of encoding the coefficients in each subband line-by-line, regions in which most of the quantized coefficients are significant are extracted by morphological dilation and encoded first. This is followed by using zerotrees to encode the remaining space which has mostly zeros. Experimental results show that the proposed algorithm is not only superior to the EZW, but also compares favorably with the most efficient wavelet-based image compression algorithms reported so far.en_US
dc.languageengen_US
dc.publisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijprai/ijprai.shtmlen_US
dc.relation.ispartofInternational Journal of Pattern Recognition and Artificial Intelligenceen_US
dc.titleAn improved embedded zerotree wavelet image coding method based on coefficient partitioning using morphological operationen_US
dc.typeArticleen_US
dc.identifier.emailLeung, CH:chleung@eee.hku.hken_US
dc.identifier.authorityLeung, CH=rp00146en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/S0218-0014(00)00049-0en_US
dc.identifier.scopuseid_2-s2.0-0034268724en_US
dc.identifier.hkuros61371-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0034268724&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume14en_US
dc.identifier.issue6en_US
dc.identifier.spage795en_US
dc.identifier.epage807en_US
dc.publisher.placeSingaporeen_US
dc.identifier.scopusauthoridZhong, J=8079523800en_US
dc.identifier.scopusauthoridLeung, CH=7402612415en_US
dc.identifier.scopusauthoridTang, YY=7404591899en_US
dc.identifier.issnl0218-0014-

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