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Optimal Neighboring Reconstruction for Hyperspectral Band Selection [PDF]
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018 Band selection, as an effective and popular dimensional reduction methods for hyperspectral image (HSI), has raised wide attention in recent years. In this paper, we propose a novel band selection method called optimal neighboring reconstruction (ONR). Compared to conventional methods, ONR mainly has following advantages.
Fahong Zhang 0003 +2 more
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Dual-Clustering-Based Hyperspectral Band Selection by Contextual Analysis [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2016 Hyperspectral image (HSI) involves vast quantities of information that can help with the image analysis. However, this information has sometimes been proved to be redundant, considering specific applications such as HSI classification and anomaly ...
Qi Wang
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Hyperspectral band selection for human detection
2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012Human detection based on spectral information is required for various applications, e.g. surveillance, tracking and missing person investigation. In practice, spectral human detection encounters the inherent challenge, i.e. multiple targets detection based on a limited number of spectral bands, because (1) there is a great variety in spectral profiles ...
Kuniaki Uto +3 more
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Fast Band Selection for Hyperspectral Imagery
2011 IEEE 17th International Conference on Parallel and Distributed Systems, 2011Band selection is a common technique for dimensionality reduction of hyperspectral imagery. When the desired object information is unknown, an unsupervised band selection approach is employed to select the most distinctive and informative bands. However, it may be time-consuming for unsupervised band selection methods that need to take all pixels into ...
He Yang, Qian Du 0001
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Dynamic band selection for hyperspectral imagery
2011 IEEE International Geoscience and Remote Sensing Symposium, 2011This paper presents a new BS, called dynamic BS (DBS) which revolutionizes the commonly used BS by considering the number of bands to be selected, p as a variable which varies with criterion used for BS and different applications. Its idea is derived from information theory where it assumes that signal sources are considered as source alphabets with ...
Keng-Hao Liu, Chein-I Chang
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Morphological Band Selection for Hyperspectral Imagery
IEEE Geoscience and Remote Sensing Letters, 2018In this letter, a novel morphological band selection method is proposed to obtain the most representative bands from hyperspectral image (HSI) in an unsupervised manner. In order to sufficiently process the HSI, we propose to use only a small set of data instead of using the original full data.
Wang, Jingyu +4 more
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Methodology for Hyperspectral Band Selection
Photogrammetric Engineering & Remote Sensing, 2004While hyperspectral data are very rich in information, processing the hyperspectral data poses several challenges regarding computational requirements, information redundancy removal, relevant information identification, and modeling accuracy.
Peter Bajcsy, Peter Groves
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Adaptive hyperspectral band selection
SPIE Proceedings, 2005We present a new technique for adaptive band selection from hyperspectral image cubes for detecting small targets using an anomaly detector. The proposed technique ensures the selection of lowest number of spectral bands using Mahalanobis distance, maximum affordable extra noise variance, and Constant False Alarm Rate (CFAR) anomaly detector threshold.
M. S. Alam, S. Ochilov
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Hyperspectral Band Selection Based on Endmember Dissimilarity for Hyperspectral Unmixing
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018Hyperspectral remote sensing could acquire hundreds of bands to cover a complete spectral interval, which deliver more information and allow a whole range of new and more precise applications. But vast data volume can cause trouble in computer processing and data transmission.
Mingming Xu 0001 +6 more
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Hyperspectral band selection based on evolutionary optimization
2013 Ninth International Conference on Natural Computation (ICNC), 2013A hyperspectral image consists of a series of spectral bands which has brought great challenges to image processing and analysis. To alleviate the curse of dimensionality, band selection is therefore applied to the hyperspectral images. In this paper, a two-step method is proposed for band selection.
Qiannan Du +3 more
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