Hyperspectral data classification improved by minimum spanning forests
Author:
Affiliation:
1. Federal University of Technology, Informatics Department, Av. Sete de Setembro 3165, Curitiba, Paraná 80230-901, Brazil
2. University of Campinas, Institute of Computing, Av. Albert Einstein 1251, Campinas, São Paulo 13083-852, Brazil
Publisher
SPIE-Intl Soc Optical Eng
Subject
General Earth and Planetary Sciences
Reference51 articles.
1. Unsupervised classification of hyperspectral-image data using fuzzy approaches that spatially exploit membership relations
Cited by 4 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. Spectral feature extraction of hyperspectral remote sensing images based on class pair-weighted criterion;Journal of Applied Remote Sensing;2019-10-31
2. Deep Cube-Pair Network for Hyperspectral Imagery Classification;Remote Sensing;2018-05-18
3. A multiscale modified minimum spanning forest method for spatial-spectral hyperspectral images classification;EURASIP Journal on Image and Video Processing;2017-11-06
4. Reweighted mass center based object-oriented sparse subspace clustering for hyperspectral images;Journal of Applied Remote Sensing;2016-11-23
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