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Using a weighted zeroblock coder for satellite image compression

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dc.contributor.authorWu, Jiaji-
dc.contributor.authorXing, Yan-
dc.contributor.authorJeong, Jechang-
dc.contributor.authorShi, Guangming-
dc.contributor.authorJiao, Licheng-
dc.date.accessioned2022-12-20T16:34:37Z-
dc.date.available2022-12-20T16:34:37Z-
dc.date.created2022-08-27-
dc.date.issued2010-07-
dc.identifier.issn1931-3195-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/174511-
dc.description.abstractIn this paper, we propose an embedded satellite image compression method using Weighted ZeroBlock Coding (WZBC) and optimal sorting. In order to reduce average codeword length, Set Partition Embedded block (SPECK) and Embedded ZeroBlock Coder (EZBC) both encode significant block-sets with fixed-length bits, while WZBC assigns different-length bits to encode block-sets which contain different numbers of significant sub-blocks. In view of the context correlation among coefficients/blocks, WZBC employs a weight context to optimize the scanning order of the significance testing and the rate-distortion performance. Experimental results show that the proposed WZBC in binary coding mode provides excellent coding performance compared with those of SPECK and Set Partitioning In Hierarchical Trees (SPIHT) which use arithmetic coding, and can even closely approach that of JPEG2000. When arithmetic coding is extensively used, the proposed method has clear advantages.-
dc.language영어-
dc.language.isoen-
dc.publisherSPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS-
dc.titleUsing a weighted zeroblock coder for satellite image compression-
dc.typeArticle-
dc.contributor.affiliatedAuthorJeong, Jechang-
dc.identifier.doi10.1117/1.3474986-
dc.identifier.scopusid2-s2.0-80054967157-
dc.identifier.wosid000281819700001-
dc.identifier.bibliographicCitationJOURNAL OF APPLIED REMOTE SENSING, v.4, pp.1 - 18-
dc.relation.isPartOfJOURNAL OF APPLIED REMOTE SENSING-
dc.citation.titleJOURNAL OF APPLIED REMOTE SENSING-
dc.citation.volume4-
dc.citation.startPage1-
dc.citation.endPage18-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEnvironmental Sciences & Ecology-
dc.relation.journalResearchAreaRemote Sensing-
dc.relation.journalResearchAreaImaging Science & Photographic Technology-
dc.relation.journalWebOfScienceCategoryEnvironmental Sciences-
dc.relation.journalWebOfScienceCategoryRemote Sensing-
dc.relation.journalWebOfScienceCategoryImaging Science & Photographic Technology-
dc.subject.keywordPlusEFFICIENT-
dc.subject.keywordAuthorcontext-based coding-
dc.subject.keywordAuthorzeroblock coding-
dc.subject.keywordAuthorweight training-
dc.subject.keywordAuthorvariable-length coding-
dc.identifier.urlhttps://www.spiedigitallibrary.org/journals/journal-of-applied-remote-sensing/volume-4/issue-1/041787/Using-a-weighted-zeroblock-coder-for-satellite-image-compression/10.1117/1.3474986.short?SSO=1-
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