Adaptive procedure of RS image classification with use of extended feature space

Nikolay G. Markov; Alexandr A. Napryushkin; Alexandr V. Zamyatin; Evgenia V. Vertinskaya

doi:10.1117/12.468219

13 March 2003 Adaptive procedure of RS image classification with use of extended feature space

Nikolay G. Markov, Alexandr A. Napryushkin, Alexandr V. Zamyatin, Evgenia V. Vertinskaya

Proceedings Volume 4885, Image and Signal Processing for Remote Sensing VIII; (2003) https://doi.org/10.1117/12.468219
Event: International Symposium on Remote Sensing, 2002, Crete, Greece

Abstract

The paper proposes an idea of the adaptive classification procedure (ACP) making the process of remotely sensed (RS) data classification more flexible and efficient in comparison with existing recognition methods. The ACP employs an improved scheme of forming feature space and adaptive decision rule allowing an optimal imagery classification method to be chosen during thematic processing. In the paper the basic principles of the ACP design and the results of its classification methods efficiency research are considered. Also the results of the ACP application for solving problems of landscape-ecological mapping of Lake Chani area (Omsk region, Russia) and Pervomayskoe oil field (Tomsk region, Russia) using multispectral images from Russian satellite RESURS-O1 are shown.

Citation Download Citation

Nikolay G. Markov, Alexandr A. Napryushkin, Alexandr V. Zamyatin, and Evgenia V. Vertinskaya "Adaptive procedure of RS image classification with use of extended feature space", Proc. SPIE 4885, Image and Signal Processing for Remote Sensing VIII, (13 March 2003); https://doi.org/10.1117/12.468219

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