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Optical Engineering

Intrinsic parallel random iteration algorithm for fractal image decoding based on iterated function system code
Author(s): Hsuan-Ting Chang; Chung J. Kuo
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Paper Abstract

A parallelized random iteration algorithm that is explicit in the iterated function system (IFS) code is proposed to speed up the decoding of fractal images. In a conventional random iteration algorithm, the fractal image is serially decoded and may generate undesirable transient points. The proposed intrinsic parallel random iteration (IPRI) algorithm determines only one initial point and can avoid the transient points. Moreover, the contractive affine transformations (CATs) denoted by the IFS code can operate in parallel and simultaneously generate subimages. The parallel capability is basically proportional to the number of CATs. Two generalized methods of the proposed IPRI algorithm are provided to solve the nonuniformity problem due to the unequal probabilities among CATs. Finally, the proposed IPRI algorithm can cooperate with a previous parallel decoding algorithm to obtain higher parallel capability. Simulation results demonstrate the validity of the proposed IPRI algorithm.

Paper Details

Date Published: 1 March 2005
PDF: 11 pages
Opt. Eng. 44(3) 037002 doi: 10.1117/1.1870392
Published in: Optical Engineering Volume 44, Issue 3
Show Author Affiliations
Hsuan-Ting Chang, National Yunlin Univ. of Science and Technology (Taiwan)
Chung J. Kuo, Delta Electronics, Inc. (Taiwan)


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