Unsupervised hyperspectral band selection with deep autoencoder unmixing

International Journal of Image and Data Fusion ◽

10.1080/19479832.2021.1972047 ◽

2021 ◽

pp. 1-18

Author(s):

Menna M. Elkholy ◽

Marwa S. Mostafa ◽

Hala M. Ebeid ◽

Mohamed Tolba

Keyword(s):

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Performance Evaluation of an Improved Multiband Impulse Radio UWB Communication System Based on Sub-Band Selection

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences ◽

10.1587/transfun.e99.a.1446 ◽

2016 ◽

Vol E99.A (7) ◽

pp. 1446-1454

Author(s):

Lin QI ◽

Masaaki KATAYAMA

Keyword(s):

Performance Evaluation ◽

Communication System ◽

Impulse Radio ◽

Band Selection ◽

Uwb Communication

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Spectral band Selection Using a Genetic Algorithm Based Wiener Filter Estimation Method for Reconstruction of Munsell Spectral Data

Electronic Imaging ◽

10.2352/issn.2470-1173.2017.18.color-059 ◽

2017 ◽

Vol 2017 (18) ◽

pp. 190-193 ◽

Author(s):

Keivan Ansari ◽

Jean-Baptiste Thomas ◽

Pierre Gouton

Keyword(s):

Genetic Algorithm ◽

Spectral Data ◽

Spectral Band ◽

Estimation Method ◽

Wiener Filter ◽

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Band selection of satellite images using Histogram distribution and Mineral Mapping using Artificial Neural Network

10.35625/cm960127x ◽

2019 ◽

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Satellite Images ◽

Band Selection ◽

Mineral Mapping ◽

Artificial Neural ◽

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Scalable One-Pass Self-Representation Learning for Hyperspectral Band Selection

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2019.2890848 ◽

2019 ◽

Vol 57 (7) ◽

pp. 4360-4374 ◽

Author(s):

Xiaohui Wei ◽

Wen Zhu ◽

Bo Liao ◽

Lijun Cai

Keyword(s):

Representation Learning ◽

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Anomaly Detection Algorithm Using Entropy-Based Band Selection and Morphological Operations for Hyperspectral Images

2020 27th International Conference on Telecommunications (ICT) ◽

10.1109/ict49546.2020.9239492 ◽

2020 ◽

Author(s):

Ferdi Andika ◽

Mia Rizkinia

Keyword(s):

Anomaly Detection ◽

Detection Algorithm ◽

Hyperspectral Images ◽

Band Selection ◽

Morphological Operations

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A Joint Landscape Metric and Error Image Approach to Unsupervised Band Selection for Hyperspectral Image Classification

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2021.3072948 ◽

2021 ◽

pp. 1-5

Author(s):

Peichao Gao ◽

Hong Zhang ◽

Zhiwei Wu ◽

Jicheng Wang

Keyword(s):

Image Classification ◽

Hyperspectral Image ◽

Band Selection ◽

Hyperspectral Image Classification ◽

Landscape Metric ◽

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A novel dependency definition exploiting boundary samples in rough set theory for hyperspectral band selection

Applied Soft Computing ◽

10.1016/j.asoc.2020.106944 ◽

2020 ◽

pp. 106944

Author(s):

Swarnajyoti Patra ◽

Barnali Barman

Keyword(s):

Rough Set ◽

Rough Set Theory ◽

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Band Selection Using Dilation Distances

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2021.3057117 ◽

2021 ◽

pp. 1-5

Author(s):

Aditya Challa ◽

Geetika Barman ◽

Sravan Danda ◽

B. S. Daya Sagar

Keyword(s):

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Hyperspectral band selection using the N-dimensional Spectral Solid Angle method for the improved discrimination of spectrally similar targets

International Journal of Applied Earth Observation and Geoinformation ◽

10.1016/j.jag.2019.03.002 ◽

2019 ◽

Vol 79 ◽

pp. 35-47 ◽

Author(s):

Yaqian Long ◽

Benoit Rivard ◽

Derek Rogge ◽

Minghua Tian

Keyword(s):

Solid Angle ◽

Band Selection ◽

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A multi-strategy integrated multi-objective artificial bee colony for unsupervised band selection of hyperspectral images

Swarm and Evolutionary Computation ◽

10.1016/j.swevo.2020.100806 ◽

2021 ◽

Vol 60 ◽

pp. 100806

Author(s):

Zhang Yong ◽

He Chun-lin ◽

Song Xian-fang ◽

Sun Xiao-yan

Keyword(s):

Artificial Bee Colony ◽

Hyperspectral Images ◽

Band Selection ◽

Multi Objective ◽

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