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Proceedings Paper

Stable construction of multiscale fuzzy-wavelet system for image recovery and compression
Author(s): Yi Yu; Shaohua Tan; Ed F. A. Deprettere
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Paper Abstract

This paper describes a convergent algorithms that is able to construct a multi-scale fuzzy-wavelet system for efficient image recovery and compression. Given only part of the original image and a prescribed compression error bound, a fuzzy system is firstly constructed at the coarsest scale. The fuzzy rules and corresponding membership functions can be stably extracted, and linguistic knowledge can also be combined with numerical one to make the scheme more flexible. Residual based wavelet system is then built to refine the performance by reaching certain fine scales. To increase the compression ratio, a reduction technique is developed to delete redundant fuzzy rules and wavelet nodes to make the whole fuzz-wavelet system as small as possible. The resulting image representation of the given image from coarse to fine scale is suitable for progressive transmission and video indexing purposes. An illustrative example is used to demonstrate the effectiveness of the scheme.

Paper Details

Date Published: 22 October 1996
PDF: 12 pages
Proc. SPIE 2846, Advanced Signal Processing Algorithms, Architectures, and Implementations VI, (22 October 1996); doi: 10.1117/12.255449
Show Author Affiliations
Yi Yu, National Univ. of Singapore (Singapore)
Shaohua Tan, National Univ. of Singapore (Singapore)
Ed F. A. Deprettere, Delft Univ. of Technology (Netherlands)


Published in SPIE Proceedings Vol. 2846:
Advanced Signal Processing Algorithms, Architectures, and Implementations VI
Franklin T. Luk, Editor(s)

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