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Proceedings Paper

Digital Image Bandwidth Compression Using Non-Parametric Predictive Filters
Author(s): G. Eichmann; M. Stojancic; L R. Chen
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Paper Abstract

A new computational technique for digital image bandwidth compression is presented. This technique is based upon the truncation of an observed image. The original image is predicted using a non-parametric approach. This predictor is a random grain allocation (RGA) algorithm, an algorithm that is similar to a Monte Carlo method. Using the RGA algorithm and with an appropriate block partitioning of the original image, significant image bit reduction can be achieved. Several image bandwidth compression examples are presented.

Paper Details

Date Published: 30 January 1990
PDF: 5 pages
Proc. SPIE 1153, Applications of Digital Image Processing XII, (30 January 1990); doi: 10.1117/12.962303
Show Author Affiliations
G. Eichmann, The City College of The City University of New York (United States)
M. Stojancic, The City College of The City University of New York (United States)
L R. Chen, The City College of The City University of New York (United States)


Published in SPIE Proceedings Vol. 1153:
Applications of Digital Image Processing XII
Andrew G. Tescher, Editor(s)

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