Land cover classification combining Sentinel-1 and Landsat 8 imagery driven by Markov random field with amendment reliability factors

Land cover classification combining Sentinel-1 and Landsat 8 imagery driven by Markov random field with amendment reliability factors

Abstract Reliability factors in Markov random field (MRF) could be used to improve classification performance for synthetic aperture radar (SAR) and optical images; however, insufficient utilization of reliability factors based on characteristics of different sources leaves more room for classificat...

Full description

Bibliographic Details
Main Authors: Xiaofei Shi, Zhiyu Deng, Xing Ding, Li Li
Format: Article
Language:English
Published: SpringerOpen 2020-05-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Markov random field
Amendment reliability factors
SAR image
Optical image
Classification
Online Access:http://link.springer.com/article/10.1186/s13638-020-01713-5

Internet

http://link.springer.com/article/10.1186/s13638-020-01713-5

Similar Items