Neural network classification with optimization by genetic algorithms for remote sensing imagery

Xiaohua Tong; Xue Zhang

doi:10.1117/12.760763

26 July 2007 Neural network classification with optimization by genetic algorithms for remote sensing imagery

Xiaohua Tong, Xue Zhang

Proceedings Volume 6752, Geoinformatics 2007: Remotely Sensed Data and Information; 67522K (2007) https://doi.org/10.1117/12.760763
Event: Geoinformatics 2007, 2007, Nanjing, China

Abstract

On the remote sensing imagery classification, the traditional methods based on statistical principle has the difficulties in distinguishing the objects with similar spectral characteristics, while the back propagation neural network method has the difficulties in sufficiency and convergence. Therefore, a new method based on neural network classification with optimization by genetic algorithms for remote sensing imagery is proposed in this paper. On the basis of the back propagation( BP )neural network classification, the optimization method by genetic algorithms is presented, including the numbers, the thresholds and the connection weights of nerve nodes of the hide layer in BP neural network. An approach on float coding with alterative length for genetic algorithms is proposed, and the evolution method is improved to obtain an optimal BP neural network. In the end, an experimental test on the remote sensing classification using TM image of Dianshan Lake is carried out, and higher classification accuracy has obtained compared to other methods, which is proved the feasibility and validity of the proposed approach.

Citation Download Citation

Xiaohua Tong and Xue Zhang "Neural network classification with optimization by genetic algorithms for remote sensing imagery", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67522K (26 July 2007); https://doi.org/10.1117/12.760763

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