Title
Effective Denoising and Classification of Hyperspectral Images Using Curvelet Transform and Singular Spectrum Analysis
Abstract
Hyperspectral imaging (HSI) classification has become a popular research topic in recent years, and effective feature extraction is an important step before the classification task. Traditionally, spectral feature extraction techniques are applied to the HSI data cube directly. This paper presents a novel algorithm for HSI feature extraction by exploiting the curvelet-transformed domain via a rela...
Year
DOI
Venue
2017
10.1109/TGRS.2016.2598065
IEEE Transactions on Geoscience and Remote Sensing
Keywords
Field
DocType
Feature extraction,Wavelet transforms,Noise reduction,Hyperspectral imaging,Spectral analysis,Principal component analysis
Computer vision,Pattern recognition,Support vector machine,Feature extraction,Hyperspectral imaging,Artificial intelligence,Singular spectrum analysis,Mathematics,Data cube,Wavelet,Wavelet transform,Curvelet
Journal
Volume
Issue
ISSN
55
1
0196-2892
Citations 
PageRank 
References 
4
0.39
0
Authors
10
Name
Order
Citations
PageRank
Tong Qiao1171.61
Jinchang Ren2114488.54
Zheng Wang3353.40
Jaime Zabalza415111.51
Meijun Sun57411.77
Huimin Zhao620623.43
Shutao Li72594139.10
Jon Atli Benediktsson84064251.17
Qingyun Dai914823.91
Stephen Marshall1022725.35