Multiscale Weighted Adjacent Superpixel-Based Composite Kernel for Hyperspectral Image Classification
This paper presents a composite kernel method (MWASCK) based on multiscale weighted adjacent superpixels (ASs) to classify hyperspectral image (HSI). The MWASCK adequately exploits spatial-spectral features of weighted adjacent superpixels to guarantee that more accurate spectral features can be ext...
Main Authors: | Yaokang Zhang, Yunjie Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-02-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/13/4/820 |
Similar Items
-
Research on land use classification of hyperspectral images based on multiscale superpixels
by: Hua Wang, et al.
Published: (2020-07-01) -
Multiscale Superpixel-Based Fine Classification of Crops in the UAV-Based Hyperspectral Imagery
by: Shuang Tian, et al.
Published: (2022-07-01) -
Multiscale Adjacent Superpixel-Based Extended Multi-Attribute Profiles Embedded Multiple Kernel Learning Method for Hyperspectral Classification
by: Lei Pan, et al.
Published: (2020-12-01) -
A Novel Spectral–Spatial Classification Method for Hyperspectral Image at Superpixel Level
by: Fuding Xie, et al.
Published: (2020-01-01) -
Local Binary Patterns and Superpixel-Based Multiple Kernels for Hyperspectral Image Classification
by: Wei Huang, et al.
Published: (2020-01-01)