The application of mixed GA-BP algorithm on remote sensing image classification

Wan-chun Zhou; Gang-sheng Xie; Bo Liu

doi:10.1117/12.813210

7 November 2008 The application of mixed GA-BP algorithm on remote sensing image classification

Wan-chun Zhou, Gang-sheng Xie, Bo Liu

Proceedings Volume 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images; 71470A (2008) https://doi.org/10.1117/12.813210
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

In this paper, both the advantage and disadvantage of traditional Genetic Algorithm and Back Propagation Algorithm are analyzed. A mixed algorithm on combination of genetic algorithm and back propagation algorithm is adopted and it's network is trained by a sample of the spectrum, texture, position and geometry features of hyperspectral remote sensing images. The numerical experiment is designed to compare GA-BP algorithm with an evolutionary BP algorithm, which is trained by Levenberg-Marquart algorithm. The results proved that GA-BP algorithm is more efficient, robust and practical.

Citation Download Citation

Wan-chun Zhou, Gang-sheng Xie, and Bo Liu "The application of mixed GA-BP algorithm on remote sensing image classification", Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470A (7 November 2008); https://doi.org/10.1117/12.813210

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