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Title: Partial differential equation-based object extraction from remote sensing imagery
Other Titles: 基于偏微分方程的遙感圖像目標提取
Authors: Li, ZB
Shi, WZ 
Keywords: Active contour
Building extraction
Level set method
Object extraction
Partial differential equation
Nonlinear diffusion
Road extraction
Issue Date: 2016
Publisher: 中國學術期刊 (光盤版) 電子雜誌社
Source: 紅外與毫米波學報 (Journal of infrared and millimeter waves), Jun. 2016, v. 35, no. 3, p. 257-262 How to cite?
Journal: 紅外與毫米波學報 (Journal of infrared and millimeter waves) 
Abstract: Object extraction is an essential task in remote sensing and geographical sciences. Previous studies mainly focused on the accuracy of object extraction method while little attention has been paid to improving their computational efficiency. For this reason,a partial differential equation( PDE)-based framework for semi-automated extraction of multiple types of objects from remote sensing imagery was proposed. The mathematical relationships among the traditional PDE-based methods,i. e.,level set method( LSM),nonlinear diffusion( NLD),and active contour( AC) were explored. It was found that both edge-and region-based PDEs are equally important for object extraction and they are generalized into a unified framework based on the derived relationships. For computational efficiency,the widely used curvature-based regularizing term is replaced by a scale space filtering. The effectiveness and efficiency of the proposed methods were corroborated by a range of promising experiments.
ISSN: 1001-9014
DOI: 10.11972/j.issn.1001-9014.2016.03.001
Rights: © 2016 China Academic Journal Electronic Publishing House. It is to be used strictly for educational and research use.
© 2016 中国学术期刊电子杂志出版社。本内容的使用仅限于教育、科研之目的。
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