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Proceedings Paper

Adaptive compression of DICOM image data
Author(s): Sergei Hludov; Thomas Engel; Christoph Meinel
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Paper Abstract

In this article a method to classify digital images into three categories based on a provisional analysis of the image content and a subsequent compression with the help of a suitable algorithm of compression is proposed. To classify the images two parameters are used. The first parameter carries the frequency information about the image. It represents the mean of the absolute amplitude of the Wavelet coefficients in the high frequency parts of the spectrum. The second parameter is an indicator concerning information about the structure of the image. The second parameter is constituted through the entropy of the length of the segments in one line and the entropy of the length of the segments in one column. In this article the results for the check of those classification rules for DICOM images are given as a confirmation of the effectiveness of the method proposed. The implementation of the image classification algorithm and the compression algorithms in the modeling process is performed in JAVA.

Paper Details

Date Published: 7 September 1998
PDF: 7 pages
Proc. SPIE 3409, Electronic Imaging: Processing, Printing, and Publishing in Color, (7 September 1998); doi: 10.1117/12.324117
Show Author Affiliations
Sergei Hludov, Institute of Telematics (Germany)
Thomas Engel, Institute of Telematics (Germany)
Christoph Meinel, Institute of Telematics (Germany)

Published in SPIE Proceedings Vol. 3409:
Electronic Imaging: Processing, Printing, and Publishing in Color
Jan Bares, Editor(s)

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