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International Journal of Biomedical Imaging - Volume 2006 2006, Article ID 83847, 27 pages



Department of Mathematics, College of Natural Science, Michigan State University, MI 48824, USA

Department of Electrical and Computer Engineering, College of Engineering, Michigan State University, MI 48824-1226, USA

Department of Radiology and Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA

Received 28 July 2005; Revised 27 October 2005; Accepted 7 November 2005

Academic Editor: Sun Yoo

Copyright © 2006 Yuhui Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This work proposes an evolution-operator-based single-time-stepmethod for image and signal processing. The key component of theproposed method is a local spectral evolution kernel LSEK thatanalytically integrates a class of evolution partial differentialequations PDEs. From the point of view PDEs, the LSEK providesthe analytical solution in a single time step, and is of spectralaccuracy, free of instability constraint. From the point ofimage-signal processing, the LSEK gives rise to a family oflowpass filters. These filters contain controllable time delay andamplitude scaling. The new evolution operator-based method isconstructed by pointwise adaptation of anisotropy to thecoefficients of the LSEK. The Perona-Malik-type of anisotropicdiffusion schemes is incorporated in the LSEK for image denoising.A forward-backward diffusion process is adopted to the LSEK forimage deblurring or sharpening. A coupled PDE system is modifiedfor image edge detection. The resulting image edge is utilized forimage enhancement. Extensive computer experiments are carried outto demonstrate the performance of the proposed method. The majoradvantages of the proposed method are its single-step solution andreadiness for multidimensional data analysis.





Autor: Yuhui Sun, Peiru Wu, G. W. Wei, and Ge Wang

Fuente: https://www.hindawi.com/



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