Hyperspectral data classification improved by minimum spanning forests

Ricardo Dutra da Silva; Helio Pedrini

doi:10.1117/1.JRS.10.025007

26 April 2016 Hyperspectral data classification improved by minimum spanning forests

Ricardo Dutra da Silva, Helio Pedrini

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 10, Issue 2, 025007 (April 2016). https://doi.org/10.1117/1.JRS.10.025007

Abstract

Remote sensing technology has applications in various knowledge domains, such as agriculture, meteorology, land use, environmental monitoring, military surveillance, and mineral exploration. The increasing advances in image acquisition techniques have allowed the generation of large volumes of data at high spectral resolution with several spectral bands representing images collected simultaneously. We propose and evaluate a supervised classification method composed of three stages. Initially, hyperspectral values and entropy information are employed by support vector machines to produce an initial classification. Then, the K-nearest neighbor technique searches for pixels with high probability of being correctly classified. Finally, minimum spanning forests are applied to these pixels to reclassify the image taking spatial restrictions into consideration. Experiments on several hyperspectral images are conducted to show the effectiveness of the proposed method.

Citation Download Citation

Ricardo Dutra da Silva and Helio Pedrini "Hyperspectral data classification improved by minimum spanning forests," Journal of Applied Remote Sensing 10(2), 025007 (26 April 2016). https://doi.org/10.1117/1.JRS.10.025007

Published: 26 April 2016

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