Cart (Loading....) | Create Account
Close category search window
 

Using MRF approach to wetland classification of high spatial resolution remote sensing imagery: A case study in Xixi Westland National Park, Hangzhou, China

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Wu Yang ; Inst. of Spatial Inf. Tech., Zhejiang Univ., Hangzhou, China ; Chunhui Wang ; Le Yu ; Dengrong Zhang

The accurate discrimination of distinct thematic classes using classification techniques developed for medium/low resolution images is not effective when apply to very high spatial resolution (HR) data (e.g. Quickbird, IKONOS) due to the spatial heterogeneity issue. In this paper, Markov random field (MRF) models, which are useful tools for integrating contextual (considering spatial dependence within and between pixels) information into classification process is used to model spatial heterogeneity for improving the classification accuracy. Two novel MRF approaches are evaluated using a Quickbird HR image covers Xixi National Wetland Park, Hangzhou, China. The experimental results show this method is effective to exact segmentation of land boundaries and suppress classification noises. In addition, the improved MRF models outperform than conventional method in terms of classification accuracy and time-efficiency.

Published in:

Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on  (Volume:2 )

Date of Conference:

28-31 Aug. 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.