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Journal of Electronic Imaging

Remote sensing image segmentation using active contours based on intercorrelation of nonsubsampled contourlet coefficients
Author(s): Lingling Fang; Xianghai Wang; Yang Sun; Kainan Xu
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Paper Abstract

Considering that remote sensing images contain rich scale-dependent information and geographical detailed information, segmentation process must be carried out under the multiscale case. The vector-valued C-V active contour model is an effective image segmentation method, but the model cannot segment the nonhomogeneous remote sensing images well. The image processing methods based on nonsubsampled contourlet transform (NSCT) can fully use the detailed information of remote sensing images. The interscale distribution characteristics of NSCT coefficients at finer scale is first analyzed and then a statistical model of signal singularities combining the coefficient correlation between intrascale and interscale is proposed. Based on the above, the vector-valued C-V active contour model is then applied to the statistical characteristics for segmenting images. Consequently, the proposed method can preserve detailed information of images and other desirable properties of active contour model. Numerical examples indicate that the proposed method is very competitive with several state-of-the-art techniques.

Paper Details

Date Published: 10 May 2016
PDF: 9 pages
J. Electron. Imaging. 25(6) 061405 doi: 10.1117/1.JEI.25.6.061405
Published in: Journal of Electronic Imaging Volume 25, Issue 6
Show Author Affiliations
Lingling Fang, Liaoning Normal Univ. (China)
Xianghai Wang, Liaoning Normal Univ. (China)
Yang Sun, Liaoning Normal Univ. (China)
Kainan Xu, Liaoning Normal Univ. (China)


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