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Comparison of Kullback-Leibler Divergence Approximation Methods Between Gaussian Mixture Models for Satellite Image Retrieval

Cui, Shiyong and Datcu, Mihai (2015) Comparison of Kullback-Leibler Divergence Approximation Methods Between Gaussian Mixture Models for Satellite Image Retrieval. In: Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2015, pp. 3719-3722. IEEE Xplore. IGARSS 2015, 26-31 July, Milan, Italy. DOI: 10.1109/IGARSS.2015.7326631

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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7326631

Abstract

In many applications, such as image retrieval and change detection, we need to assess the similarity of two statistical models. As a distance measure between two probability density functions, Kullback-Leibler divergence is widely used for comparing two statistical models. Unfortunately, for some models such as Gaussian Mixture Model (GMM), Kullback-Leibler divergence has no analytically tractable formula. We have to resort to approximation methods. In this paper, we compare seven methods, namely Monte Carlo method, matched bond approximation, product of Gaussian, variational method, unscented transformation, Gaussian approximation, and min-Gaussian approximation, for approximating the Kullback-Leibler divergence between two Gaussian mixture models for satellite image retrieval. Two image retrieval experiments based on two publicly available datasets have been performed. The comparison is carried out in terms of both retrieval performance and computational time.

Item URL in elib:https://elib.dlr.de/96179/
Document Type:Conference or Workshop Item (Speech)
Title:Comparison of Kullback-Leibler Divergence Approximation Methods Between Gaussian Mixture Models for Satellite Image Retrieval
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Cui, ShiyongRemote Sensing Technology Institute (IMF)UNSPECIFIED
Datcu, MihaiRemote Sensing Technology Institute (IMF)UNSPECIFIED
Date:July 2015
Journal or Publication Title:Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2015
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2015.7326631
Page Range:pp. 3719-3722
Editors:
EditorsEmail
UNSPECIFIEDIEEE Org.
Publisher:IEEE Xplore
Status:Published
Keywords:Gaussian Mixture Model (GMM), Kullback-Leibler Divergence, Image Retrieval.
Event Title:IGARSS 2015
Event Location:Milan, Italy
Event Type:international Conference
Event Dates:26-31 July
Organizer:IEEE Org.
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:06 May 2015 13:03
Last Modified:31 Jul 2019 19:52

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