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Feature based non parametric estimation of Kullback Leibler divergence for SAR image change detection

Cui, Shiyong and Luo, Chengfeng (2016) Feature based non parametric estimation of Kullback Leibler divergence for SAR image change detection. Remote Sensing Letters, 7 (11), pp. 1102-1111. Informa Ltd. DOI: 10.1080/2150704X.2016.1212418 ISSN 2150-704X

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Official URL: http://www.tandfonline.com/doi/full/10.1080/2150704X.2016.1212418

Abstract

In this article, a method based on a non-parametric estimation of the Kullback–Leibler divergence using a local feature space is proposed for synthetic aperture radar (SAR) image change detection. First, local features based on a set of Gabor filters are extracted from both pre- and post-event images. The distribution of these local features from a local neighbourhood is considered as a statistical representation of the local image information. The Kullback–Leibler divergence as a probabilistic distance is used for measuring the similarity of the two distributions. Nevertheless, it is not trivial to estimate the distribution of a high-dimensional random vector, let alone the comparison of two distributions. Thus, a non-parametric method based on k-nearest neighbour search is proposed to compute the Kullback–Leibler divergence between the two distributions. Through experiments, this method is compared with other state-of-the-art methods and the effectiveness of the proposed method for SAR image change detection is demonstrated.

Item URL in elib:https://elib.dlr.de/105700/
Document Type:Article
Title:Feature based non parametric estimation of Kullback Leibler divergence for SAR image change detection
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Cui, ShiyongRemote Sensing Technology Institute (IMF)https://orcid.org/0000-0002-5417-4482
Luo, ChengfengChinese Academy of Surveying and Mapping (CASM)https://orcid.org/0000-0002-5857-2226
Date:August 2016
Journal or Publication Title:Remote Sensing Letters
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:7
DOI :10.1080/2150704X.2016.1212418
Page Range:pp. 1102-1111
Publisher:Informa Ltd
ISSN:2150-704X
Status:Published
Keywords:Synthetic aperture radar (SAR), Kullback-Leibler divergence, Change detection, Nonparametric estimation, k-nearest neighbor
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Cui, Shiyong
Deposited On:12 Aug 2016 13:40
Last Modified:31 Jul 2019 20:02

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