An unsupervised support vector method for change detection

F. Bovolo; G. Camps-Valls; L. Bruzzone

doi:10.1117/12.737764

24 October 2007 An unsupervised support vector method for change detection

F. Bovolo, G. Camps-Valls, L. Bruzzone

Proceedings Volume 6748, Image and Signal Processing for Remote Sensing XIII; 674809 (2007) https://doi.org/10.1117/12.737764
Event: SPIE Remote Sensing, 2007, Florence, Italy

Abstract

This paper formulates the problem of distinguishing changed from unchanged pixels in remote sensing images as a minimum enclosing ball (MEB) problem with changed pixels as target class. The definition of the sphere shaped decision boundary with minimal volume that embraces changed pixels is approached in the context the support vector formalism adopting a support vector domain description (SVDD) one-class classifier. The SVDD maps the data into a high dimensional feature space where the spherical support of the high dimensional distribution of changed pixels is computed. The proposed formulation of the SVDD uses both target and outlier samples for defining the MEB, and is included here in an unsupervised system for change detection. For this purpose, nearly certain examples for the classes of both targets (i.e., changed pixels) and outliers (i.e., unchanged pixels) for training are identified based on thresholding the magnitude of spectral change vectors. Experimental results obtained on two different multitemporal and multispectral remote sensing images pointed out the effectiveness of the proposed method.

Citation Download Citation

F. Bovolo, G. Camps-Valls, and L. Bruzzone "An unsupervised support vector method for change detection", Proc. SPIE 6748, Image and Signal Processing for Remote Sensing XIII, 674809 (24 October 2007); https://doi.org/10.1117/12.737764

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available