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Edge and Mean Based Image Compression

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dc.creator Desai, Ujjaval Y.
dc.creator Mizuki, Marcelo M.
dc.creator Masaki, Ichiro
dc.creator Horn, Berthold K.P.
dc.date 2004-10-04T14:15:47Z
dc.date 2004-10-04T14:15:47Z
dc.date 1996-11-01
dc.date.accessioned 2013-10-09T02:42:04Z
dc.date.available 2013-10-09T02:42:04Z
dc.date.issued 2013-10-09
dc.identifier AIM-1584
dc.identifier http://hdl.handle.net/1721.1/5943
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description In this paper, we present a static image compression algorithm for very low bit rate applications. The algorithm reduces spatial redundancy present in images by extracting and encoding edge and mean information. Since the human visual system is highly sensitive to edges, an edge-based compression scheme can produce intelligible images at high compression ratios. We present good quality results for facial as well as textured, 256~x~256 color images at 0.1 to 0.3 bpp. The algorithm described in this paper was designed for high performance, keeping hardware implementation issues in mind. In the next phase of the project, which is currently underway, this algorithm will be implemented in hardware, and new edge-based color image sequence compression algorithms will be developed to achieve compression ratios of over 100, i.e., less than 0.12 bpp from 12 bpp. Potential applications include low power, portable video telephones.
dc.format 11 p.
dc.format 2864296 bytes
dc.format 790595 bytes
dc.format application/postscript
dc.format application/pdf
dc.language en_US
dc.relation AIM-1584
dc.subject AI
dc.subject MIT
dc.subject Artificial Intelligence
dc.title Edge and Mean Based Image Compression


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