Results 281 to 290 of about 109,853 (338)

Evaluating Approximations of River Channel Shape Using a National Cross‐Section Database

Water Resources Research, Volume 62, Issue 5, May 2026.
Abstract Many hydrologic applications require basic information on the size and shape of river channels, but measuring cross section (XS) geometry in the field or via remote sensing can be costly and often provides only partial coverage. Given these challenges, we capitalized upon an existing data set of 46,971 XS from gaging stations to evaluate ...
C. J. Legleiter, P. J. Kinzel
wiley   +1 more source

Enhancing Hyperspectral Data Throughput Utilizing Wavelet-Based Fingerprints

, 1999
I.W. Ginsberg
openalex   +1 more source

AI‐Enabled Imaging for Pathogen Detection Under Stress Conditions: A Systematic Review

Comprehensive Reviews in Food Science and Food Safety, Volume 25, Issue 3, May 2026.
ABSTRACT Advances in pathogen detection that incorporate artificial intelligence (AI) may capture microbial signals under challenging environmental conditions that traditional methods miss. This systematic review evaluates the application, performance, and methodological characteristics of AI‐enabled imaging for pathogen detection, including its impact
MeiLi Papa, Gillian Kuehnle, Yoo Jung (Erika) Oh, Jiyoon Yi   +3 more
wiley   +1 more source

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Symbolic representation of hyperspectral data

Applied Optics, 1987
We have developed a symbolic representation of hyperspectral data using the scale space techniques of Witkin. We created a scale space image of hyperspectral data from convolution with Gaussian masks and then a fingerprint that extracts individual features from the original data.
M A, Piech, K R, Piech
openaire   +2 more sources

Watermarking of hyperspectral data

IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2004
Watermarking is drawing the interest of researchers in many areas due to developments in sharing resources. Watermarked data helps protect ownership rights and provides a means of detecting illegal use. In this paper, an adaptive watermarking method based on the Redundant Discrete Wavelet Transform (RDWT) is proposed and applied to hyperspectral ...
H. Tamhankar, L.M. Bruce, N. Younan
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Modeling hyperspectral imaging data

SPIE Proceedings, 2003
Developing proper models for hyperspectral imaging (HSI) data allows for useful and reliable algorithms for data exploitation. These models provide the foundation for development and evaluation of detection, classification, clustering, and estimation algorithms. To date, real world HSI data has been modeled as a single multivariate Gaussian, however it
David B. Marden, Dimitris G. Manolakis
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Processing of hyperspectral data

2023
Hyperspectral imagery is becoming increasingly important in remote sensing. Traditional airborne or ground-based hyperspectral imagery is more often complemented by satellite imagery. The technology for production and miniaturisation of hyperspectral sensors has advanced to the point where relatively high quality imagery can be acquired from unmanned ...
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Hyperspectral Image Sharpening Using Multispectral Data

2007 IEEE Aerospace Conference, 2005
Multispectral sharpening of hyperspectral imagery fuses the spectral content of the hyperspectral image with the spatial and spectral content of the multispectral image. The approach we have been investigating compares the spectral information present in the multispectral image to the spectral content in the hyperspectral image and derives a set of ...
Michael E. Winter, Edwin M. Winter, Scott G. Beaven, Anthony J. Ratkowski   +3 more
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Processing misregistered hyperspectral data

SPIE Proceedings, 2007
Many hyperspectral sensors collect data using multiple spectrometers to span a broad spectral range. These spectrometers can be fed by optical fibers on the same or separate focal planes. The Modular Imaging Spectrometer Instrument (MISI), a 70 band line scanner built by the Rochester Institute of Technology, is configured in this manner. Visible
Jason T. Casey, Stephen R. Lach, John P. Kerekes   +2 more
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Hyperspectral Data Compression

2006
Hyperspectral Data Compression provides a survey of recent results in the field of compression of remote sensed 3D data, with a particular interest in hyperspectral imagery.Chapter 1 addresses compression architecture, and reviews and compares compression methods.
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