Lossless medical-image compression using multiple array technique
The multiple array technique proposed in this paper is a lossless compression technique that involves no transformation, and achieves a very good compression ratio. This technique is based on forming three arrays to indicate and code the changes in the adjacent pixels. The arrays thus formed can be...
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| creator | Devaraj, K. Munukur, R.K. Kesavamurthy, T. |
| description | The multiple array technique proposed in this paper is a lossless compression technique that involves no transformation, and achieves a very good compression ratio. This technique is based on forming three arrays to indicate and code the changes in the adjacent pixels. The arrays thus formed can be further compressed using Huffman coding. The computational complexity is greatly reduced thus producing faster compressions and decompressions. Due to the combination of simplicity and compression potential of this technique, the algorithm "enjoys the best of both worlds". This technique attains compression ratios similar to or superior than the lossless image compression standards presently available. Due to the high compression ratio, the average bits required to represent a pixel is greatly reduced. Thus, this algorithm is optimally suited for telemedicine having fast transmission rates. |
| doi_str_mv | 10.1109/ISPACS.2005.1595540 |
| format | Conference Proceeding |
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This technique is based on forming three arrays to indicate and code the changes in the adjacent pixels. The arrays thus formed can be further compressed using Huffman coding. The computational complexity is greatly reduced thus producing faster compressions and decompressions. Due to the combination of simplicity and compression potential of this technique, the algorithm "enjoys the best of both worlds". This technique attains compression ratios similar to or superior than the lossless image compression standards presently available. Due to the high compression ratio, the average bits required to represent a pixel is greatly reduced. 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This technique is based on forming three arrays to indicate and code the changes in the adjacent pixels. The arrays thus formed can be further compressed using Huffman coding. The computational complexity is greatly reduced thus producing faster compressions and decompressions. Due to the combination of simplicity and compression potential of this technique, the algorithm "enjoys the best of both worlds". This technique attains compression ratios similar to or superior than the lossless image compression standards presently available. Due to the high compression ratio, the average bits required to represent a pixel is greatly reduced. Thus, this algorithm is optimally suited for telemedicine having fast transmission rates.</description><subject>Biomedical imaging</subject><subject>Educational institutions</subject><subject>Fourier transforms</subject><subject>Gray Array</subject><subject>Huffman coding</subject><subject>Image coding</subject><subject>Image reconstruction</subject><subject>Image storage</subject><subject>Lossless Image Compression</subject><subject>Medical Image Compression</subject><subject>Multiple Array Technique</subject><subject>Redundancy</subject><subject>Telemedicine</subject><subject>Wavelet transforms</subject><isbn>0780392663</isbn><isbn>9780780392663</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj8tqwzAURAWlkDbNF2SjH7B7Jeu5NKaPgKGFNOugyDepivyoZS_y9zU0ZzPDLIYZQrYMcsbAPu_2n2W1zzmAzJm0Ugq4I4-gDRSWK1WsyCalH1gQUgiAB1LWfUoRU6ItNsG7mIXWXZD6vh3GJQ59R-cUugtt5ziFISJ14-iudEL_3YXfGZ_I_dnFhJubrsnh9eWres_qj7ddVdZZYFpOmfFc-QVjEY33mjcaTwylBIcIqpFKW30WTlssFHilnBLM4OI4U_qkizXZ_vcGRDwO47JzvB5vL4s_f15Jpw</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Devaraj, K.</creator><creator>Munukur, R.K.</creator><creator>Kesavamurthy, T.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2005</creationdate><title>Lossless medical-image compression using multiple array technique</title><author>Devaraj, K. ; Munukur, R.K. ; Kesavamurthy, T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-8c26cccc89ee8cc72d7eb1e550aee06d56797f4a79e360c66a6418e0c62167b73</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Biomedical imaging</topic><topic>Educational institutions</topic><topic>Fourier transforms</topic><topic>Gray Array</topic><topic>Huffman coding</topic><topic>Image coding</topic><topic>Image reconstruction</topic><topic>Image storage</topic><topic>Lossless Image Compression</topic><topic>Medical Image Compression</topic><topic>Multiple Array Technique</topic><topic>Redundancy</topic><topic>Telemedicine</topic><topic>Wavelet transforms</topic><toplevel>online_resources</toplevel><creatorcontrib>Devaraj, K.</creatorcontrib><creatorcontrib>Munukur, R.K.</creatorcontrib><creatorcontrib>Kesavamurthy, T.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Devaraj, K.</au><au>Munukur, R.K.</au><au>Kesavamurthy, T.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Lossless medical-image compression using multiple array technique</atitle><btitle>2005 International Symposium on Intelligent Signal Processing and Communication Systems</btitle><stitle>ISPACS</stitle><date>2005</date><risdate>2005</risdate><spage>837</spage><epage>840</epage><pages>837-840</pages><isbn>0780392663</isbn><isbn>9780780392663</isbn><abstract>The multiple array technique proposed in this paper is a lossless compression technique that involves no transformation, and achieves a very good compression ratio. This technique is based on forming three arrays to indicate and code the changes in the adjacent pixels. The arrays thus formed can be further compressed using Huffman coding. The computational complexity is greatly reduced thus producing faster compressions and decompressions. Due to the combination of simplicity and compression potential of this technique, the algorithm "enjoys the best of both worlds". This technique attains compression ratios similar to or superior than the lossless image compression standards presently available. Due to the high compression ratio, the average bits required to represent a pixel is greatly reduced. Thus, this algorithm is optimally suited for telemedicine having fast transmission rates.</abstract><pub>IEEE</pub><doi>10.1109/ISPACS.2005.1595540</doi><tpages>4</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Biomedical imaging Educational institutions Fourier transforms Gray Array Huffman coding Image coding Image reconstruction Image storage Lossless Image Compression Medical Image Compression Multiple Array Technique Redundancy Telemedicine Wavelet transforms |
| title | Lossless medical-image compression using multiple array technique |
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