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 Russia satellite RESURS-O1 are shown.
| Original language | English |
|---|---|
| Pages (from-to) | 489-500 |
| Number of pages | 12 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 4885 |
| DOIs | |
| Publication status | Published - 1 Dec 2002 |
| Event | Image and Signal Processing for Remote Sensing VII - Agia Pelagia, Greece Duration: 24 Sep 2002 → 27 Sep 2002 |
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Keywords
- Digital image analysis
- Neural networks
- Nonparametric statistics
- Pattern recognition
- Texture analysis
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering
Cite this
Adaptive procedure of RS images classification with use of extended feature space. / Markov, Nikolay G.; Napryushkin, Alexandr A.; Zamyatin, Alexandr V.; Vertinskaya, Evgenia V.
In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 4885, 01.12.2002, p. 489-500.Research output: Contribution to journal › Conference article
}
TY - JOUR
T1 - Adaptive procedure of RS images classification with use of extended feature space
AU - Markov, Nikolay G.
AU - Napryushkin, Alexandr A.
AU - Zamyatin, Alexandr V.
AU - Vertinskaya, Evgenia V.
PY - 2002/12/1
Y1 - 2002/12/1
N2 - 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 Russia satellite RESURS-O1 are shown.
AB - 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 Russia satellite RESURS-O1 are shown.
KW - Digital image analysis
KW - Neural networks
KW - Nonparametric statistics
KW - Pattern recognition
KW - Texture analysis
UR - http://www.scopus.com/inward/record.url?scp=0038627485&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0038627485&partnerID=8YFLogxK
U2 - 10.1117/12.468219
DO - 10.1117/12.468219
M3 - Conference article
VL - 4885
SP - 489
EP - 500
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
SN - 0277-786X
ER -