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Proceedings Paper

Image compression using partitioned iterated function systems
Author(s): Guojun Lu; Toon Lin Yew
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Paper Abstract

The Partitioned Iterated Function Systems (PIFS) involves partitioning a image into non-overlapping range blocks and overlapping domain blocks. For each range block, a matching domain block is found by applying a contractive affine transformation. The set of transformations uniquely defines an estimation of the original image. In this paper, we investigate the quadtree partition technique of generating range blocks. In this technique, a range block is recursively partitioned into 4 equally sized sub-squares, when it is not covered well enough by a domain. But this method has a inherent penalty in which the existence of range blocks of different sizes requires the storage of the sizes and coordinates of the range blocks. We present a scheme that stores the required decoding information with very little overhead. One of the properties offractals is that detail exists at every scale. This has led us to investigate into the possibility of exploiting the scalability property of fractals to allow us to improve the compression time and ratio.

Paper Details

Date Published: 1 May 1994
PDF: 12 pages
Proc. SPIE 2186, Image and Video Compression, (1 May 1994); doi: 10.1117/12.173912
Show Author Affiliations
Guojun Lu, National Univ. of Singapore (Singapore)
Toon Lin Yew, National Univ. of Singapore (Singapore)


Published in SPIE Proceedings Vol. 2186:
Image and Video Compression
Majid Rabbani; Robert J. Safranek, Editor(s)

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