Results 11 to 20 of about 23,100 (259)
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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Bathymetric-Based Band Selection Method for Hyperspectral Underwater Target Detection
Remote Sensing, 2021 Band selection has imposed great impacts on hyperspectral image processing in recent years. Unfortunately, few existing methods are proposed for hyperspectral underwater target detection (HUTD).
Jiahao Qi +6 more
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Problem-based band selection for hyperspectral images [PDF]
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017 This paper addresses the band selection of a hyperspectral image. Considering a binary classification, we devise a method to choose the more discriminating bands for the separation of the two classes involved, by using a simple algorithm: single-layer neural network. After that, the most discriminative bands are selected, and the resulting reduced data
Habermann, Mateus +2 more
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Band Ranking via Extended Coefficient of Variation for Hyperspectral Band Selection
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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Hyperspectral Band Selection Using Improved Classification Map [PDF]
IEEE Geoscience and Remote Sensing Letters, 2017 Although it is a powerful feature selection algorithm, the wrapper method is rarely used for hyperspectral band selection. Its accuracy is restricted by the number of labeled training samples and collecting such label information for hyperspectral image is time consuming and expensive.
Xianghai Cao +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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An improved cuckoo search-based adaptive band selection for hyperspectral image classification
European Journal of Remote Sensing, 2020 The information in hyperspectral images usually has a strong correlation, a large number of bands, which lead to the “curse of dimensionality”. So, band selection is usually used to address this issue. However, problems remain for band selection, such as
Shiwei Shao
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Remote Sensing, 2022 It has been widely certified that hyperspectral images can be effectively used to monitor soil organic matter (SOM). Though numerous bands reveal more details in spectral features, information redundancy and noise interference also come accordingly.
Linya Zhao +6 more
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Hyper-Graph Regularized Kernel Subspace Clustering for Band Selection of Hyperspectral Image
IEEE Access, 2020 Band selection is an effective way to deal with the problem of the Hughes phenomenon and high computation complexity in hyperspectral image (HSI) processing. Based on the hypothesis that all the pixels are sampled from the union of subspaces, many robust
Meng Zeng +5 more
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Correlation-Guided Ensemble Clustering for Hyperspectral Band Selection
Remote Sensing, 2022 Hyperspectral band selection is a commonly used technique to alleviate the curse of dimensionality. Recently, clustering-based methods have attracted much attention for their effectiveness in selecting informative and representative bands.
Wenguang Wang, Wenhong Wang, Hongfu Liu
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