EBARec-BS: Effective Band Attention Reconstruction Network for Hyperspectral Imagery Band Selection [PDF]
Remote Sensing, 2021 Hyperspectral band selection (BS) is an effective means to avoid the Hughes phenomenon and heavy computational burden in hyperspectral image processing.
Yufei Liu +3 more
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A new band selection framework for hyperspectral remote sensing image classification [PDF]
Scientific ReportsDimensionality Reduction (DR) is an indispensable step to enhance classifier accuracy with data redundancy in hyperspectral images (HSI). This paper proposes a framework for DR that combines band selection (BS) and effective spatial features.
B. L. N. Phaneendra Kumar +4 more
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SSANet-BS: Spectral–Spatial Cross-Dimensional Attention Network for Hyperspectral Band Selection
Remote SensingBand selection (BS) aims to reduce redundancy in hyperspectral imagery (HSI). Existing BS approaches typically model HSI only in a single dimension, either spectral or spatial, without exploring the interactions between different dimensions. To this end,
Chuanyu Cui +3 more
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Unsupervised Hyperspectral Band Selection Using Spectral–Spatial Iterative Greedy Algorithm [PDF]
SensorsHyperspectral band selection (BS) is an important technique to reduce data dimensionality for the classification applications of hyperspectral remote sensing images (HSIs). Recently, searching-based BS methods have received increasing attention for their
Xin Yang, Wenhong Wang
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BAND SELECTION OF HYPERSPECTRAL IMAGES BASED ON MARKOV CLUSTERING AND SPECTRAL DIFFERENCE MEASUREMENT FOR OBJECT EXTRACTION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 For the existing hyperspectral image (HSI) band selection (BS) algorithm does not consider the strong correlation between adjacent bands and does not meet the high-precision extraction of single target, a HSI BS algorithm based on Markov clustering and ...
T. Zhang +14 more
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BS-Nets: An End-to-End Framework for Band Selection of Hyperspectral Image [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2020 The paper has been submitted to IEEE ...
Yaoming Cai, Xiaobo Liu, Zhihua Cai
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Remote Sensing, 2022 Band subset selection (BSS) is one of the ways to implement band selection (BS) for a hyperspectral image (HSI). Different from conventional BS methods, which select bands one by one, BSS selects a band subset each time and preserves the best one from ...
Keng-Hao Liu +2 more
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Nonlocal Band Attention Network for Hyperspectral Image Band Selection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Band selection (BS) is a foundational problem for the analysis of high-dimensional hyperspectral image (HSI) cubes. Recent developments in the visual attention mechanism allow for specifically modeling the complex relationship among different components.
Tiancong Li +4 more
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Quality control of Aloe vera (Aloe barbadensis) and Aloe ferox using band-selective quantitative heteronuclear single quantum correlation spectroscopy (bs-qHSQC) [PDF]
Talanta, 2019 In the present study, band-selective quantitative heteronuclear single quantum correlation spectroscopy (bs-qHSQC) was applied for the quality control of the two Aloe species present in the European Pharmacopeia. After development and validation of a complete spectral range (csr-) qHSQC assay, a specific pulse program with selective excitation was ...
Ulrich, Girreser +2 more
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Open Geosciences, 2020 Swarm intelligence algorithms have been widely used in the dimensional reduction of hyperspectral remote sensing imagery. The ant colony algorithm (ACA), the clone selection algorithm (CSA), particle swarm optimization (PSO), and the genetic algorithm ...
Xiaohui Ding +4 more
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