SAR change detection based on Generalized Gamma distribution divergence and auto-threshold segmentation(WSANE 2009 (Workshop for Space, Aeronautical and Navigational Electronics))

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概要

• 論文の詳細を見る

• This paper first utilizes generalized Gamma model to fit the statistical characteristics of co-registered SAR images. Then, extract the difference map through measuring the similarity between PDFs by Kullback-Leibler Divergence. Afterwards, apply a combination of KS & KL test to evaluate and choose fitting function of the difference map for the model-based KI threshold segmentation automatically. Experiment was carried on the multi temporal SAR images for Olympic Village of Beijing, acquired by TerraSAR-X and Radarsat-2, as well as Shunyi District of Beijing, acquired by Envisat-ASAR. Such results confirmed the proposed method is more sensitive in detecting regions that have no variance in mean value, but differ in texture, than traditional methods

• 2009-10-26

著者

• Wang Chao

  Center For Earth Observation And Digital Earth Cas

• GAO Cong-shan

  Center for Earth Observation and Digital Earth, CAS

• ZHANG Hong

  Center for Earth Observation and Digital Earth, CAS

• ZHANG Bo

  Center for Earth Observation and Digital Earth, CAS

• Gao Cong-shan

  Center For Earth Observation And Digital Earth Cas:graduate University Of Chinese Academy Of Science

• Zhang Hong

  Center For Earth Observation And Digital Earth Cas Beijing

• Zhang Bo

  Center For Earth Observation And Digital Earth Cas

関連論文

• SAR change detection based on Generalized Gamma distribution divergence and auto-threshold segmentation(WSANE 2009 (Workshop for Space, Aeronautical and Navigational Electronics))
• Morphometric Analysis of Neurocentral Synchondrosis Using Magnetic Resonance Imaging in the Normal Skeletally Immature Spine

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