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Edge and Mean Based Image Compression

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.

Identiferoai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/5943
Date01 November 1996
CreatorsDesai, Ujjaval Y., Mizuki, Marcelo M., Masaki, Ichiro, Horn, Berthold K.P.
Source SetsM.I.T. Theses and Dissertation
Languageen_US
Detected LanguageEnglish
Format11 p., 2864296 bytes, 790595 bytes, application/postscript, application/pdf
RelationAIM-1584

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