Band Subset Selection Approaches Based On Sparse Representation for Hyperspectral Imagery
碩士 === 國立中山大學 === 機械與機電工程學系研究所 === 107 === With the advancement of remote sensing technology, the applications of hyperspectral imagery (HSI) are more and more popular. Despite of many success achieved by HSI techniques, there are still some problems to be solved. For instance, HSI data provides hug...
Main Authors: | Meng-Han Lu, 呂孟翰 |
---|---|
Other Authors: | Keng-Hao Liu |
Format: | Others |
Language: | zh-TW |
Published: |
2018
|
Online Access: | http://ndltd.ncl.edu.tw/handle/un37mu |
Similar Items
-
A Symmetric Sparse Representation Based Band Selection Method for Hyperspectral Imagery Classification
by: Weiwei Sun, et al.
Published: (2016-03-01) -
Unsupervised Band Selection of Hyperspectral Images via Multi-Dictionary Sparse Representation
by: Fei Li, et al.
Published: (2018-01-01) -
Low rank and sparse representation for hyperspectral imagery analysis
by: Sumarsono, Alex
Published: (2015) -
Band Subset Selection for Hyperspectral Image Classification
by: Chunyan Yu, et al.
Published: (2018-01-01) -
Hyperspectral imagery super-resolution by sparse representation and spectral regularization
by: Zhao Yongqiang, et al.
Published: (2011-01-01)