Image compression using partitioned iterated function systems

Guojun Lu; Toon Lin Yew

doi:10.1117/12.173912

1 May 1994 Image compression using partitioned iterated function systems

Guojun Lu, Toon Lin Yew

Proceedings Volume 2186, Image and Video Compression; (1994) https://doi.org/10.1117/12.173912
Event: IS&T/SPIE 1994 International Symposium on Electronic Imaging: Science and Technology, 1994, San Jose, CA, United States

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.

Citation Download Citation

Guojun Lu and Toon Lin Yew "Image compression using partitioned iterated function systems", Proc. SPIE 2186, Image and Video Compression, (1 May 1994); https://doi.org/10.1117/12.173912

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