Abstract
The discrimination ability of four different methods for texture computation in ERS SAR imagery is examined and compared. Feature selection methodology and discriminant analysis are applied to find the optimal combination of texture features. By combining features derived from different texture models, the classification accuracy increased significantly.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Geoscience and Remote Sensing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
