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Conference Paper: High compression ratio image processing techniques using combinations of WT and IFS

TitleHigh compression ratio image processing techniques using combinations of WT and IFS
Authors
KeywordsCommunications
Issue Date1996
PublisherIEEE.
Citation
The 3rd International Conference on Signal Processing, Beijing, China, 14-18 October 1996. In Conference Proceedings, 1996, v. 2, p. 843-846 How to Cite?
AbstractMany works of compressing image based on wavelet transformation have been presented in recent years. Also, the method of fractals is used in this field. The first method uses the pyramid subband decomposition, and the second takes advantage of the self-similarity between the basic image and subimages. We combine these two methods as a hybrid algorithm to complete the image compression. The experiments show that this method has a better performance than many others, especially, in a high compression ratio situation. A comparison with the famous embedded zero tree wavelet (EZW) algorithm shows that its performance is close to the EZW algorithm.
Persistent Identifierhttp://hdl.handle.net/10722/46000
ISBN

 

DC FieldValueLanguage
dc.contributor.authorZhang, YGen_HK
dc.contributor.authorLi, XJen_HK
dc.contributor.authorNg, TSen_HK
dc.date.accessioned2007-10-30T06:40:21Z-
dc.date.available2007-10-30T06:40:21Z-
dc.date.issued1996en_HK
dc.identifier.citationThe 3rd International Conference on Signal Processing, Beijing, China, 14-18 October 1996. In Conference Proceedings, 1996, v. 2, p. 843-846en_HK
dc.identifier.isbn0-7803-2912-0en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46000-
dc.description.abstractMany works of compressing image based on wavelet transformation have been presented in recent years. Also, the method of fractals is used in this field. The first method uses the pyramid subband decomposition, and the second takes advantage of the self-similarity between the basic image and subimages. We combine these two methods as a hybrid algorithm to complete the image compression. The experiments show that this method has a better performance than many others, especially, in a high compression ratio situation. A comparison with the famous embedded zero tree wavelet (EZW) algorithm shows that its performance is close to the EZW algorithm.en_HK
dc.format.extent828523 bytes-
dc.format.extent21012 bytes-
dc.format.extent21377 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofInternational Conference on Signal Processing Proceedings-
dc.rights©1996 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.subjectCommunicationsen_HK
dc.titleHigh compression ratio image processing techniques using combinations of WT and IFSen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0-7803-2912-0&volume=2&spage=843&epage=846&date=1996&atitle=High+compression+ratio+image+processing+techniques+using+combinations+of+WT+and+IFSen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICSIGP.1996.566217en_HK
dc.identifier.hkuros26738-

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