Results 11 to 20 of about 314,709 (295)
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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An Improved Ant Colony Algorithm for Optimized Band Selection of Hyperspectral Remotely Sensed Imagery [PDF]
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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Attend in Bands: Hyperspectral Band Weighting and Selection for Image Classification [PDF]
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019 Hyperspectral remote sensing sensors have the ability to capture a wide range of spectrum of ground objects with hundreds to thousands of bands. The obtained hyperspectral images contain more detailed spectral information than conventional panchromatic or color images.
Jing Wang 0062 +2 more
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Learning-Based Optimization of Hyperspectral Band Selection for Classification [PDF]
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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Bathymetric-Based Band Selection Method for Hyperspectral Underwater Target Detection [PDF]
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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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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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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Similarity-Based Hyperspectral Band Selection Using Deep Reinforcement Learning [PDF]
, 2022 The main goal of hyperspectral band selection is to select a subset of bands to reduce the redundancy in hyperspectral images. Deep reinforcement learning was recently introduced for this task, which adopts a deep Q-network as the agent and information ...
Tuxworth, Gervase, Zhou, Jun, Bao, Dong
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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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