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...

Full description

Bibliographic Details
Main Authors: Lei Pan, Chengxun He, Yang Xiang, Le Sun
Format: Article
Language:English
Published: MDPI AG 2020-12-01
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

Similar Items

Similar Items