Sparsity Regularized Deep Subspace Clustering for Multicriterion-Based Hyperspectral Band Selection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral images provide rich spectral information corresponding to visible and near-infrared imaging regions, facilitating accurate classification, object identification, and target detection. However, the high volume of data creates a computational
Samiran Das +3 more
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Constrained-Target Band Selection With Subspace Partition for Hyperspectral Target Detection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Hyperspectral target detection is widely used in both military and civilian fields. In practical applications, how to select a low-correlation and representative band subset to reduce redundancy is worth discussing.
Xudong Sun +4 more
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Underwater Hyperspectral Target Detection with Band Selection
Remote Sensing, 2020 Compared to multi-spectral imagery, hyperspectral imagery has very high spectral resolution with abundant spectral information. In underwater target detection, hyperspectral technology can be advantageous in the sense of a poor underwater imaging ...
Xianping Fu +5 more
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Fusion of Various Band Selection Methods for Hyperspectral Imagery
Remote Sensing, 2019 This paper presents an approach to band selection fusion (BSF) which fuses bands produced by a set of different band selection (BS) methods for a given number of bands to be selected, nBS.
Yulei Wang +3 more
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An Unsupervised Band Selection Method via Contrastive Learning for Hyperspectral Images
Remote Sensing, 2023 Band selection (BS) is an efficacious approach to reduce hyperspectral information redundancy while preserving the physical meaning of hyperspectral images (HSIs).
Xiaorun Li +3 more
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Efficient Graph Convolutional Self-Representation for Band Selection of Hyperspectral Image
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Hyperspectral image (HSI) band selection (BS) is an important task for HSI dimensionality reduction, whose goal is to select an informative band subset containing less redundancy.
Yaoming Cai +3 more
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Progressive Sample Processing of Band Selection for Hyperspectral Image Transmission
Remote Sensing, 2018 Band selection (BS) is one of the important topics in hyperspectral image (HSI) processing. Many types of BS algorithms were proposed in the last decade. However, most of them were designed for off-line use. They can only be used with pre-collected data,
Keng-Hao Liu +3 more
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Multiple Band Prioritization Criteria-Based Band Selection for Hyperspectral Imagery
Remote Sensing, 2022 Band selection (BS) is an effective pre-processing way to reduce the redundancy of hyperspectral data. Specifically, the band prioritization (BP) criterion plays an essential role since it can judge the importance of bands from a particular perspective ...
Xudong Sun +3 more
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MIMO Self-Heterodyne OFDM Using Band Selection Technique
Entropy, 2020 The 5G technology is a promising technology to cope with the increasing demand for higher data rate and quality of service. In this paper, two proposed techniques are implemented for multiple input multiple output (MIMO) self-heterodyne OFDM system to ...
Amira I. Zaki +3 more
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Hyperspectral Image Band Selection Based on CNN Embedded GA (CNNeGA)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Hyperspectral images (HSIs) are a powerful source of reliable data in various remote sensing applications. But due to the large number of bands, HSI has information redundancy, and methods are often used to reduce the number of spectral bands.
Mohammad Esmaeili +4 more
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