A Structural Subspace Clustering Approach for Hyperspectral Band Selection [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Band selection, which removes irrelevant bands from hyperspectral images (HSIs) and keeps essential spectral information contained in a relatively few bands, allows huge savings in data storage, computation time, and imaging hardware. In this article, we propose a novel structural subspace clustering (STSC) method for hyperspectral band selection ...
Shaoguang Huang +2 more
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Unsupervised Band Selection Based on Evolutionary Multiobjective Optimization for Hyperspectral Images [PDF]
, 2016 Band selection is an important preprocessing step for hyperspectral image processing. Many valid criteria have been proposed for band selection, and these criteria model band selection as a single-objective optimization problem.
Yuan, Yuan +2 more
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Hyperspectral Band Selection via Band Grouping and Adaptive Multi-Graph Constraint
Remote Sensing, 2022 Unsupervised band selection has gained increasing attention recently since massive unlabeled high-dimensional data often need to be processed in the domains of machine learning and data mining.
Mengbo You +5 more
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Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking [PDF]
, 2016 Saliency detection has been a hot topic in recent years, and many efforts have been devoted in this area. Unfortunately, the results of saliency detection can hardly be utilized in general applications.
Lin, Jianzhe, Yuan, Yuan, Wang, Qi
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Optimal Clustering Framework for Hyperspectral Band Selection [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2018 Band selection, by choosing a set of representative bands in hyperspectral image (HSI), is an effective method to reduce the redundant information without compromising the original contents. Recently, various unsupervised band selection methods have been proposed, but most of them are based on approximation algorithms which can only obtain suboptimal ...
Qi Wang 0009 +2 more
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Hyperspectral Band Selection via Optimal Combination Strategy
Remote Sensing, 2022 Band selection is one of the main methods of reducing the number of dimensions in a hyperspectral image. Recently, various methods have been proposed to address this issue.
Shuying Li +3 more
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Hyperspectral image band selection via global optimal clustering [PDF]
, 2017 Band selection, by choosing a set of representative bands in hyperspectral images (HSI), is concerned to be an effective method to eliminate the 'Hughes phenomenon'.
Fahong Zhang +5 more
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A wavelet-based band selection method for hyperspectral image classification [PDF]
, 2023 This paper presents an adaptive wavelet-based band selection method for hyperspectral image classification, that simultaneously selects relevant bands by analysing few spectral signatures of classes of interest. The properties of the wavelet transform in
Giuseppina Monteverde +4 more
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Unsupervised Band Selection Method Based on Importance-Assisted Column Subset Selection
IEEE Access, 2019 Band selection is an important preprocessing technique for hyperspectral images to select a band subset with representative information and low correlation. However, most methods focus on removing redundant components without loss of original information,
Xiaoyan Luo +3 more
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A survey of band selection techniques for hyperspectral image classification
Journal of Spectral Imaging, 2020 Hyperspectral images usually contain hundreds of contiguous spectral bands, which can precisely discriminate the various spectrally similar classes. However, such high-dimensional data also contain highly correlated and irrelevant information, leading to
Shrutika S. Sawant, Manoharan Prabukumar
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