Segmentation of dust storm areas on Mars images using principal component analysis and neural network

Segmentation of dust storm areas on Mars images using principal component analysis and neural network

Abstract We present a method for automated segmentation of dust storm areas on Mars images observed by an orbiter. We divide them into small patches. Normal basis vectors are obtained from the many small patches by principal component analysis. We train a classifier using coefficients of these basis...

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Bibliographic Details
Main Authors: Ryusei Gichu, Kazunori Ogohara
Format: Article
Language:English
Published: SpringerOpen 2019-02-01
Series:Progress in Earth and Planetary Science
Subjects:
Mars
Dust storm
Segmentation
Machine learning
Principal component analysis
Online Access:http://link.springer.com/article/10.1186/s40645-019-0266-1

Internet

http://link.springer.com/article/10.1186/s40645-019-0266-1

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