A Variational Level Set SAR Image Segmentation Approach Based on Statistical Model

Cao  Zong-Jie; Min  Rui; Pang  Ling-Li; Pi Yi-Ming

doi:10.3724/SP.J.1146.2007.00823

Volume 30 Issue 12

Jan. 2011

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Article Navigation > Journal of Electronics & Information Technology > 2008 > 30(12): 2862-2866

Cao Zong-Jie, Min Rui, Pang Ling-Li, Pi Yi-Ming. A Variational Level Set SAR Image Segmentation Approach Based on Statistical Model[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2862-2866. doi: 10.3724/SP.J.1146.2007.00823

Citation:

Cao Zong-Jie, Min Rui, Pang Ling-Li, Pi Yi-Ming. A Variational Level Set SAR Image Segmentation Approach Based on Statistical Model[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2862-2866. doi: 10.3724/SP.J.1146.2007.00823

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A Variational Level Set SAR Image Segmentation Approach Based on Statistical Model

doi: 10.3724/SP.J.1146.2007.00823

Received Date: 2007-05-28
Rev Recd Date: 2008-04-07
Publish Date: 2008-12-19

Abstract

Abstract

In this paper, a variational level set approach for segmentation of Regions Of Interest (ROI) is presented. Following the analysis of the SAR image characteristic, a new energy functional is defined by importing the statistical model of speckle noise. The energy functional is with respect to level set function, which is obviously different from the energy functional with respect to parameterized curve in general level set approach. The segmentation of ROI is implemented by the numerical solution of the Partial Difference Equations (PDEs) that are derived by minimizing the energy formulation. The performance of the approach is verified by both synthetic and real SAR images. It shows that the approach has the advantage of importing the noise information in the energy definition, thus accurately extracting the ROI from SAR image but without any speckle pre-processing step.
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References(1)

References

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