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Proceedings Paper

Medical image compression using a new subband coding method
Author(s): Faouzi Kossentini; Mark J. T. Smith; Allen Scales; Douglas M. Tucker
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Paper Abstract

A recently introduced iterative complexity- and entropy-constrained subband quantization design algorithm is generalized and applied to medical image compression. In particular, the corresponding subband coder is used to encode computed tomography (CT) axial slice head images, where statistical dependencies between neighboring image subbands are exploited. Inter-slice conditioning is also employed for further improvements in compression performance. The subband coder features many advantages such as relatively low complexity and operation over a very wide range of bit rates. Experimental results demonstrate that the performance of the new subband coder is relatively good, both objectively and subjectively.

Paper Details

Date Published: 27 April 1995
PDF: 11 pages
Proc. SPIE 2431, Medical Imaging 1995: Image Display, (27 April 1995); doi: 10.1117/12.207652
Show Author Affiliations
Faouzi Kossentini, Georgia Institute of Technology (United States)
Mark J. T. Smith, Georgia Institute of Technology (United States)
Allen Scales, Nichols Research Corp. (United States)
Douglas M. Tucker, Univ. of Alabama/Birmingham (United States)


Published in SPIE Proceedings Vol. 2431:
Medical Imaging 1995: Image Display
Yongmin Kim, Editor(s)

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