Nonlocal Band Attention Network for Hyperspectral Image Band Selection [PDF]
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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Y–Net: Identification of Typical Diseases of Corn Leaves Using a 3D–2D Hybrid CNN Model Combined with a Hyperspectral Image Band Selection Module [PDF]
Sensors, 2023 Corn diseases are one of the significant constraints to high–quality corn production, and accurate identification of corn diseases is of great importance for precise disease control.
Yinjiang Jia +3 more
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Band Selection for Dehazing Algorithms Applied to Hyperspectral Images in the Visible Range [PDF]
Sensors, 2021 Images captured under bad weather conditions (e.g., fog, haze, mist, dust, etc.), suffer from poor contrast and visibility, and color distortions. The severity of this degradation depends on the distance, the density of the atmospheric particles and the ...
Sol Fernández-Carvelo +5 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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BSDR: A Data-Efficient Deep Learning-Based Hyperspectral Band Selection Algorithm Using Discrete Relaxation [PDF]
SensorsHyperspectral band selection algorithms are crucial for processing high-dimensional data, which enables dimensionality reduction, improves data analysis, and enhances computational efficiency.
Mohammad Rahman +4 more
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Incorporating band selection in the spatial selection of spectral endmembers
International Journal of Applied Earth Observations and Geoinformation, 2020 The impact of band selection on endmember selection is seldom explored in the analysis of hyperspectral imagery. This study incorporates the N-dimensional Spectral Solid Angle (NSSA) band selection tool into the Spectral-Spatial Endmember Extraction ...
Yaqian Long, Benoit Rivard, Derek Rogge
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Representative Band Selection for Hyperspectral Image Classification
ISPRS International Journal of Geo-Information, 2018 The high dimensionality of hyperspectral images (HSIs) brings great difficulty for their later data processing. Band selection, as a commonly used dimension reduction technique, is the selection of optimal band combinations from the original bands, while
Fuding Xie +3 more
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Band Ranking via Extended Coefficient of Variation for Hyperspectral Band Selection [PDF]
Remote Sensing, 2020 Hundreds of narrow bands over a continuous spectral range make hyperspectral imagery rich in information about objects, while at the same time causing the neighboring bands to be highly correlated.
Peifeng Su +2 more
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Improved SR-SSIM Band Selection Method Based on Band Subspace Partition
Remote Sensing, 2023 Scholars have performed much research on reducing the redundancy of hyperspectral data. As a measure of the similarity between hyperspectral bands, structural similarity is used in band selection methods.
Tingrui Hu +3 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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