Biased reconstruction of wavelet coefficients in JPEG2000 decoding
Lossy wavelet compression with JPEG2000 results in the loss of information through coefficient quantization. When decoding a lossy JPEG2000 compressed image, the exact original value of a quantized coefficient is unknown to the decoder, which must try to optimally assign a reconstruction value to th...
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description | Lossy wavelet compression with JPEG2000 results in the loss of information through coefficient quantization. When decoding a lossy JPEG2000 compressed image, the exact original value of a quantized coefficient is unknown to the decoder, which must try to optimally assign a reconstruction value to the coefficient within the appropriate quantization interval. Typically, JPEG2000 decoders reconstruct a wavelet coefficient at the midpoint of its quantization interval. In this paper, alternative reconstruction algorithms are proposed that utilize statistics accumulated throughout decoding to improve the selection of reconstruction points. Biased reconstruction algorithms are described for zero-quantized coefficients as well as non-zero-quantized coefficients. The computational complexity of the algorithms is also analyzed. At bit rates ranging from 0.25-2 bits per pixel, the proposed techniques yield PSNR improvements on average of 0.1-0.15 dB relative to midpoint reconstruction. |
doi_str_mv | 10.1109/ICIP.2002.1038951 |
format | Conference Proceeding |
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When decoding a lossy JPEG2000 compressed image, the exact original value of a quantized coefficient is unknown to the decoder, which must try to optimally assign a reconstruction value to the coefficient within the appropriate quantization interval. Typically, JPEG2000 decoders reconstruct a wavelet coefficient at the midpoint of its quantization interval. In this paper, alternative reconstruction algorithms are proposed that utilize statistics accumulated throughout decoding to improve the selection of reconstruction points. Biased reconstruction algorithms are described for zero-quantized coefficients as well as non-zero-quantized coefficients. The computational complexity of the algorithms is also analyzed. At bit rates ranging from 0.25-2 bits per pixel, the proposed techniques yield PSNR improvements on average of 0.1-0.15 dB relative to midpoint reconstruction.</description><identifier>ISSN: 1522-4880</identifier><identifier>ISBN: 9780780376229</identifier><identifier>ISBN: 0780376226</identifier><identifier>EISSN: 2381-8549</identifier><identifier>DOI: 10.1109/ICIP.2002.1038951</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; Computational complexity ; Decoding ; Image coding ; Image reconstruction ; Quantization ; Reconstruction algorithms ; Statistics ; Transform coding ; Wavelet coefficients</subject><ispartof>Proceedings. 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When decoding a lossy JPEG2000 compressed image, the exact original value of a quantized coefficient is unknown to the decoder, which must try to optimally assign a reconstruction value to the coefficient within the appropriate quantization interval. Typically, JPEG2000 decoders reconstruct a wavelet coefficient at the midpoint of its quantization interval. In this paper, alternative reconstruction algorithms are proposed that utilize statistics accumulated throughout decoding to improve the selection of reconstruction points. Biased reconstruction algorithms are described for zero-quantized coefficients as well as non-zero-quantized coefficients. The computational complexity of the algorithms is also analyzed. At bit rates ranging from 0.25-2 bits per pixel, the proposed techniques yield PSNR improvements on average of 0.1-0.15 dB relative to midpoint reconstruction.</description><subject>Algorithm design and analysis</subject><subject>Computational complexity</subject><subject>Decoding</subject><subject>Image coding</subject><subject>Image reconstruction</subject><subject>Quantization</subject><subject>Reconstruction algorithms</subject><subject>Statistics</subject><subject>Transform coding</subject><subject>Wavelet coefficients</subject><issn>1522-4880</issn><issn>2381-8549</issn><isbn>9780780376229</isbn><isbn>0780376226</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2002</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9js0OgjAQhDf-JBLlAYyXvgC4LaDtFYKKJw_eDYHF1GgxFDW-vT1wdjLJHCZfZgCWHEPOUa2LrDiFAlGEHCOpEj4CT0SSBzKJ1Rh8tZXoHG03QqgJeDwRIoilxBn41t7QKU5ix3uQprq0VLOOqtbYvntVvW4Naxv2Kd90p55VLTWNrjSZ3jJt2PGU7902stohtTbXBUyb8m7JH3IOq11-zg6BJqLLs9OPsvtehqfR__YHqts89g</recordid><startdate>2002</startdate><enddate>2002</enddate><creator>Deever, A.T.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2002</creationdate><title>Biased reconstruction of wavelet coefficients in JPEG2000 decoding</title><author>Deever, A.T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_10389513</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Algorithm design and analysis</topic><topic>Computational complexity</topic><topic>Decoding</topic><topic>Image coding</topic><topic>Image reconstruction</topic><topic>Quantization</topic><topic>Reconstruction algorithms</topic><topic>Statistics</topic><topic>Transform coding</topic><topic>Wavelet coefficients</topic><toplevel>online_resources</toplevel><creatorcontrib>Deever, A.T.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Deever, A.T.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Biased reconstruction of wavelet coefficients in JPEG2000 decoding</atitle><btitle>Proceedings. International Conference on Image Processing</btitle><stitle>ICIP</stitle><date>2002</date><risdate>2002</risdate><volume>3</volume><spage>III</spage><epage>III</epage><pages>III-III</pages><issn>1522-4880</issn><eissn>2381-8549</eissn><isbn>9780780376229</isbn><isbn>0780376226</isbn><abstract>Lossy wavelet compression with JPEG2000 results in the loss of information through coefficient quantization. When decoding a lossy JPEG2000 compressed image, the exact original value of a quantized coefficient is unknown to the decoder, which must try to optimally assign a reconstruction value to the coefficient within the appropriate quantization interval. Typically, JPEG2000 decoders reconstruct a wavelet coefficient at the midpoint of its quantization interval. In this paper, alternative reconstruction algorithms are proposed that utilize statistics accumulated throughout decoding to improve the selection of reconstruction points. Biased reconstruction algorithms are described for zero-quantized coefficients as well as non-zero-quantized coefficients. The computational complexity of the algorithms is also analyzed. At bit rates ranging from 0.25-2 bits per pixel, the proposed techniques yield PSNR improvements on average of 0.1-0.15 dB relative to midpoint reconstruction.</abstract><pub>IEEE</pub><doi>10.1109/ICIP.2002.1038951</doi></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Algorithm design and analysis Computational complexity Decoding Image coding Image reconstruction Quantization Reconstruction algorithms Statistics Transform coding Wavelet coefficients |
title | Biased reconstruction of wavelet coefficients in JPEG2000 decoding |
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