Classification of high-spatial resolution imagery based on distance-weighted Markov random field with an improved iterated conditional mode method

Author:

Zhang Qian1,Zhang Liangpei1,Huang Xin1

Affiliation:

1. a State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University , 129 Luoyu Road, Wuhan , 430079 , China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Remote Sensing Image Change Detection Based on Density Attraction and Multi-Scale and Multi-Feature Fusion;Laser & Optoelectronics Progress;2019

2. An Active Relearning Framework for Remote Sensing Image Classification;IEEE Transactions on Geoscience and Remote Sensing;2018-06

3. Natural Polymers: Tissue Engineering;Concise Encyclopedia of Biomedical Polymers and Polymeric Biomaterials;2017-08-16

4. Rate-aware network codes for completion time reduction in device-to-device communications;2016 IEEE International Conference on Communications (ICC);2016-05

5. An MRF Model-Based Active Learning Framework for the Spectral-Spatial Classification of Hyperspectral Imagery;IEEE Journal of Selected Topics in Signal Processing;2015-09

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