Results 11 to 20 of about 296,860 (257)
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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Crop Classification for Agricultural Applications in Hyperspectral Remote Sensing Images
Applied Sciences, 2022 Hyperspectral imaging (HSI), measuring the reflectance over visible (VIS), near-infrared (NIR), and shortwave infrared wavelengths (SWIR), has empowered the task of classification and can be useful in a variety of application areas like agriculture, even
Loganathan Agilandeeswari +4 more
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HYBASE: hyperspectral band selection [PDF]
SPIE Proceedings, 2009 Band selection is essential in the design of multispectral sensor systems. This paper describes the TNO hyperspectral band selection tool HYBASE. It calculates the optimum band positions given the number of bands and the width of the spectral bands.
Schwering, P.B.W. +2 more
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Fluorescence Hyperspectral Imaging for Early Diagnosis of Heat-Stressed Ginseng Plants
Applied Sciences, 2022 Ginseng is a perennial herbaceous plant that has been widely consumed for medicinal and dietary purposes since ancient times. Ginseng plants require shade and cool temperatures for better growth; climate warming and rising heat waves have a negative ...
Mohammad Akbar Faqeerzada +7 more
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Progressive band selection [PDF]
SPIE Proceedings, 2009 Progressive band selection (PBS) reduces spectral redundancy without significant loss of information, thereby reducing hyperspectral image data volume and processing time. Used onboard a spacecraft, it can also reduce image downlink time. PBS prioritizes an image's spectral bands according to priority scores that measure their significance to a ...
Kevin Fisher, Chein-I Chang
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EBARec-BS: Effective Band Attention Reconstruction Network for Hyperspectral Imagery Band Selection
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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Learning-Based Optimization of Hyperspectral Band Selection for Classification
Remote Sensing, 2023 Hyperspectral sensors acquire spectral responses from objects with a large number of narrow spectral bands. The large volume of data may be costly in terms of storage and computational requirements.
Cemre Omer Ayna +3 more
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IEEE Access, 2020 The ant colony algorithm (ACA) has been widely used for reducing the dimensionality of hyperspectral remote sensing imagery. However, the ACA suffers from problems of slow convergence and of local optima (caused by loss of population diversity).
Xiaohui Ding +6 more
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Dual Homogeneous Patches-Based Band Selection Methodology for Hyperspectral Classification
Remote Sensing, 2023 Homogeneous band- or pixel-based feature selection, which exploits the difference between spectral or spatial regions to select informative and low-redundant bands, has been extensively studied in classifying hyperspectral images (HSIs).
Xianyue Wang +3 more
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Editorial for Special Issue “Hyperspectral Imaging and Applications”
Remote Sensing, 2019 Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging.
Chein-I Chang +3 more
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