Local edge detectors using a sigmoidal transformation for piecewise smooth data

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초록

For piecewise smooth data, edges can be recognized by jump discontinuities in the data. Successful edge detection is essential in digital signal processing as the most relevant information is often observed near the edges in each segmented region. In this paper, using the concentration property of existing local edge detectors and the clustering property of sigmoidal transformations, we provide enhanced edge detectors which diminish the oscillations of the local detector near jump discontinuities as well as highly improve rate of convergence away from the discontinuities. Numerical results of some examples illustrate efficiency of the presented method. (C) 2012 Elsevier Ltd. All rights reserved.

키워드

Jump discontinuityLocal edge detectorConcentration propertySigmoidal transformationClustering propertyFOURIER-SERIESSPECTRAL DATAINTEGRATION
제목
Local edge detectors using a sigmoidal transformation for piecewise smooth data
저자
Yun, Beong InRim, Kyung Soo
DOI
10.1016/j.aml.2012.09.006
발행일
2013-02
유형
Article
저널명
Applied Mathematics Letters
26
2
페이지
270 ~ 276