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Proceedings Paper

Quantitative evaluation of wavelet-based image processing algorithms
Author(s): Zhenxue Jing; Yisheng Zheng; Walter Huda; Andrew F. Laine; Jian Fan; Yunong Xing
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Paper Abstract

Wavelet analysis is currently being investigated as an image enhancement tool for use in mammography. Although this approach to image processing appears to have great promise, there remain major uncertainties regarding an optimal form of wavelet based algorithms. It is, therefore, desirable to have a quantitative method for evaluating a wavelet based image processing algorithm. Optimization of algorithms prior to evaluation using standard Receiver Operating Characteristic method is made possible. A mathematical method has been developed where the input signal is a gaussian with added random noise. An enhancement factor (EF) is obtained from input and output signal-to-noise ratios, SNRi and SNRo, (EF equals SNRo/SNRi). The development and testing of this method is described, and a practical application in given showing the major features of a wavelet based image processing algorithm based on the Frazier-Jawerth transform.

Paper Details

Date Published: 11 October 1994
PDF: 10 pages
Proc. SPIE 2303, Wavelet Applications in Signal and Image Processing II, (11 October 1994); doi: 10.1117/12.188807
Show Author Affiliations
Zhenxue Jing, Univ. of Florida (United States)
Yisheng Zheng, Univ. of Florida (United States)
Walter Huda, Univ. of Florida (United States)
Andrew F. Laine, Univ. of Florida (United States)
Jian Fan, Univ. of Florida (United States)
Yunong Xing, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 2303:
Wavelet Applications in Signal and Image Processing II
Andrew F. Laine; Michael A. Unser, Editor(s)

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