Academic Commons

Articles

Quantitative evaluation of wavelet-based image processing algorithms

Jing, Zhenxue; Zheng, Yisheng; Huda, Walter; Laine, Andrew F.; Fan, Jian; Xing, Yunong

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.

Files

Also Published In

Title
Wavelet applications in signal and image processing II : 27-29 July 1994, San Diego, California ; Proceedings of SPIE, vol. 2303
DOI
https://doi.org/10.1117/12.188807

More About This Work

Academic Units
Biomedical Engineering
Publisher
SPIE
Published Here
August 25, 2010
Academic Commons provides global access to research and scholarship produced at Columbia University, Barnard College, Teachers College, Union Theological Seminary and Jewish Theological Seminary. Academic Commons is managed by the Columbia University Libraries.