A new tolerant rough set on remote sensing data classification

Liwei Li; Liping Lei; Jianwen Ma

doi:10.1117/12.873203

3 November 2010 A new tolerant rough set on remote sensing data classification

Liwei Li, Liping Lei, Jianwen Ma

Proceedings Volume 7841, Sixth International Symposium on Digital Earth: Data Processing and Applications; 78410A (2010) https://doi.org/10.1117/12.873203
Event: The Sixth International Symposium on Digital Earth, 2009, Beijing, China

Abstract

Image classification is an important technique in the digital earth. This paper gives a comprehensive study on a new proposed tolerant rough set classification method. Its essence lies in introducing the idea of k-nearest neighbors into the construction of rough set. Experiment is carried out with Landsat-5 TM image of eastern Beijing. Classification result is analyzed in detail and compared with that of the current tolerant rough set method. Outcome indicates that the method is more interpretable and reliable, and is good at handling uncertainty in the process of satellite remote sensing data classification. Also it is a promising tool at classifying areas with complex spectral feature distribution.

Citation Download Citation

Liwei Li, Liping Lei, and Jianwen Ma "A new tolerant rough set on remote sensing data classification", Proc. SPIE 7841, Sixth International Symposium on Digital Earth: Data Processing and Applications, 78410A (3 November 2010); https://doi.org/10.1117/12.873203

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