Results 261 to 270 of about 36,270 (292)

Dimensionality reduction in hyperspectral imagery

SPIE Proceedings, 2003
In this paper we examine how the projection of hyperspectral data into smaller dimensional subspaces can effect the propagation of error. In particular, we show that the nonorthogonality of endmembers in the linear mixing model can cause small changes in band space (as, for example, from the addition of noise) to lead to relatively large changes in the
David Gillis, Jeffrey H. Bowles, Michael E. Winter   +2 more
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Interest segmentation of hyperspectral imagery

2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2010
In recent years, many new methods for analyzing spectral imagery have been introduced. These new methods have been developed to improve the analysis of hyperspectral imagery. Many of these techniques are data driven anomaly/target detection and spectral clustering algorithms which are used to decide whether a particular pixel or area is “interesting ...
Ariel Schlamm, David Messinger, William Basener   +2 more
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Anomaly Detection in Hyperspectral Imagery

2016
In this chapter we are presenting the literature and proposed approaches for anomaly detection in hyperspectral images. These approaches are grouped into four categories based on the underlying techniques used to achieve the detection: 1) the statistical based methods, 2) the kernel based methods, 3) the feature selection based methods and 4) the ...
Karim Saheb Ettabaa, Manel Ben Salem
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Coastal Characterization from Hyperspectral Imagery

Imaging and Applied Optics Congress, 2010
Coastal mapping products and models from hyperspectral remote sensing experiments in different coastal types are compared: barrier island coast (Virginia, 2007), coral coast (Hawaii 2009), mangrove coast (Australia, 2009), and coral limestone and volcanic coasts (Guam and CNMI, 2010). Article not available.
Charles M. Bachmann, C. Reid. Nichols, Marcos J. Montes, Robert A. Fusina, John C. Fry, Rong-Rong Li, Deric Gray, Daniel Korwan, Christopher Parrish, Jon Sellars, Stephen A. White, Jason Woolard, Krista Lee, Cecilia McConnon, Jon Wende   +14 more
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Lossless Compression of Hyperspectral Imagery

2011 First International Conference on Data Compression, Communications and Processing, 2011
In this paper we review the Spectral oriented Least SQuares (SLSQ) algorithm : an efficient and low complexity algorithm for Hyper spectral Image loss less compression, presented in [2]. Subsequently, we consider two important measures : Pearson's Correlation and Bhattacharyya distance and describe a band ordering approach based on this distances ...
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Multiscale, multivariate autoregressive detection for hyperspectral imagery

Proceedings of SPIE, 2009
There are often demands for region target detection such as air pollution detection and oil spills monitoring, even though small target detection has gained much attention in the field of hyper spectral detection. In this paper, we present a multiscale-multivariate autoregressive (MMA) method to handle such region targets, considering the spatial ...
Lin He, Wei Di, Zhuliang Yu, Yuanqing Li, Zhenghui Gu   +4 more
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Finding Endmembers in Hyperspectral Imagery

2016
Endmembers, defined as pure signatures, can be used to specify distinct spectral classes of interest in the data, thus providing crucial information in hyperspectral data exploitation. Technically speaking, an endmember is generally considered as a calibrated spectral signature in a data base or spectral library and is not necessarily to be a real data
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Compression of hyperspectral imagery via linear prediction

2006
Motta et al., 2003) proposed a Locally Optimal Vector Quantizer (LPVQ) for lossless encoding of hyperspectral data, in particular, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images. In this paper we first show how it is possible to improve the baseline LPVQ algorithm via linear prediction techniques, band reordering and least squares ...
FRANCESCO RIZZO, CARPENTIERI, Bruno, GIOVANNI MOTTA, JAMES A. STORER   +3 more
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The New Hyperspectral Satellite PRISMA: Imagery for Forest Types Discrimination

Sensors, 2021
Elia Vangi, Giovanni D'amico, Saverio Francini   +2 more
exaly  

Target detection of hyperspectral imagery

Eighth Symposium on Novel Photoelectronic Detection Technology and Applications, 2022
Hang Qu, Lei Xiao, Xinghua Hou
openaire   +1 more source