Autoregressive model for multi-pass SAR change detection based on image stacks

Bruna G. Palm; Dimas I. Alves; Viet T. Vu; Mats I. Pettersson; Fabio M. Bayer; Renato J. Cintra; Renato Machado; Patrik Dammert; Hans Hellsten

doi:10.1117/12.2325661

9 October 2018 Autoregressive model for multi-pass SAR change detection based on image stacks

Bruna G. Palm, Dimas I. Alves, Viet T. Vu, Mats I. Pettersson, Fabio M. Bayer, Renato J. Cintra, Renato Machado, Patrik Dammert, Hans Hellsten

Author Affiliations +

Proceedings Volume 10789, Image and Signal Processing for Remote Sensing XXIV; 1078916 (2018) https://doi.org/10.1117/12.2325661
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Change detection is an important synthetic aperture radar (SAR) application, usually used to detect changes on the ground scene measurements in different moments in time. Traditionally, change detection algorithm (CDA) is mainly designed for two synthetic aperture radar (SAR) images retrieved at different instants. However, more images can be used to improve the algorithms performance, witch emerges as a research topic on SAR change detection. Image stack information can be treated as a data series over time and can be modeled by autoregressive (AR) models. Thus, we present some initial findings on SAR change detection based on image stack considering AR models. Applying AR model for each pixel position in the image stack, we obtained an estimated image of the ground scene which can be used as a reference image for CDA. The experimental results reveal that ground scene estimates by the AR models is accurate and can be used for change detection applications.

Citation Download Citation

Bruna G. Palm, Dimas I. Alves, Viet T. Vu, Mats I. Pettersson, Fabio M. Bayer, Renato J. Cintra, Renato Machado, Patrik Dammert, and Hans Hellsten "Autoregressive model for multi-pass SAR change detection based on image stacks", Proc. SPIE 10789, Image and Signal Processing for Remote Sensing XXIV, 1078916 (9 October 2018); https://doi.org/10.1117/12.2325661

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