Multiscale Adjacent Superpixel-Based Extended Multi-Attribute Profiles Embedded Multiple Kernel Learning Method for Hyperspectral Classification

Multiscale Adjacent Superpixel-Based Extended Multi-Attribute Profiles Embedded Multiple Kernel Learning Method for Hyperspectral Classification

In this paper, superpixel features and extended multi-attribute profiles (EMAPs) are embedded in a multiple kernel learning framework to simultaneously exploit the local and multiscale information in both spatial and spectral dimensions for hyperspectral image (HSI) classification. First, the origin...

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Bibliographic Details
Main Authors: Lei Pan, Chengxun He, Yang Xiang, Le Sun
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Remote Sensing
Subjects:
hyperspectral classification
extended multi-attribute profiles
multiple kernel learning
superpixel segmentation
Online Access:https://www.mdpi.com/2072-4292/13/1/50

Internet

https://www.mdpi.com/2072-4292/13/1/50

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