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Prediction accuracy of color imagery from hyperspectral imagery

Peter Bajcsy, Rob Kooper, Sylvia S. Shen, Paul E. Lewis
2005 Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI  
In this paper we present the utilization of high-spectral resolution imagery for improving low-spectral resolution imagery.  ...  Finally, we evaluate two color cameras by establishing ground truth RGB values from hyperspectral imagery and by defining pixel-based, correlation-based and histogram-based error metrics.  ...  ACKNOWLEDGEMENTS This material is based upon work partially supported by the National Center for Advanced Secure Systems Research (NCASSR), and the National Laboratory for Advanced Data Research (NLADR  ... 
doi:10.1117/12.602925 fatcat:5qhyacwffvadnonqfgcig5zbcy

Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca & G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)

I N S Jaya
2014 Jurnal Manajemen Hutan Tropika  
Chapter 3 is dealing with the use of hyperspectral image for assessing carbon dynamic and biodiversity of forest, while Chapter 9 describes the use of hyperspectral data for assessing the recovery following  ...  The most practicable use of hyperspectral for measurement, reporting and verification of tropical forest For practical purposes, the presence of hyperspectral imagery will significantly contribute the  ... 
doi:10.7226/jtfm.20.1.66 fatcat:gitviukcxng3dita3c2bctl7dm

Hyperspectral image visualization based on high dynamic range imaging

Secil Suer, Hatice Koc, Sarp Erturk
2014 2014 22nd Signal Processing and Communications Applications Conference (SIU)  
ABSTRACT Hyperspectral imaging captures a high number of spectrally narrow bands and provides advantages for image analysis applications such as identification and classification in particular.  ...  A novel hyperspectral visualization approach based on high dynamic range imaging is presented in this paper.  ...  Ramanath, "Band selection using independent component analysis for hyperspectral image processing," in Proc. 32nd Appl. Imagery Pattern Recog. Workshop, Washington, DC, pp. 93-99, Oct. 2003.  ... 
doi:10.1109/siu.2014.6830442 dblp:conf/siu/SuerKE14 fatcat:gwiosktjwje6zno4xoyw36fd7u

Special Section Guest Editorial: Airborne Hyperspectral Remote Sensing of Urban Environments

Qian Du, Paolo Gamba
2014 Journal of Applied Remote Sensing  
One paper studies the impact of dimensionality reduction (through band selection) on classification accuracy, which is "Ant colony optimization-based supervised and unsupervised band selections for hyperspectral  ...  "Dynamic classifier selection using spectral-spatial information for hyperspectral image classification" by Su et al. proposes the integration of spectral features with volumetric textural features to  ...  spectrometer imagery."  ... 
doi:10.1117/1.jrs.8.085001 fatcat:4qmlzbgqvbc6fmsmbossq5yw34

Foreword to the Special Issue on Hyperspectral Remote Sensing and Imaging Spectroscopy

S. Prasad, W. Liao, M. He, J. Chanussot
2018 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Chakravortty et al. present a subpixel timeseries hyperspectral analysis approach for dynamic mangrove eco-system monitoring.  ...  In Du et al. a low-rank matrix factorization based approach is paired with a band-specific noise model for hyperspectral denoising.  ...  Chakravortty et al. present a subpixel timeseries hyperspectral analysis approach for dynamic mangrove eco-system monitoring.  ... 
doi:10.1109/jstars.2018.2820938 fatcat:pqu6zhrl3rc3tm7tqpi4p4t34m

Identification of invasive vegetation using hyperspectral imagery in the shore of the Kinu River, Japan

Shan LU, Yo SHIMIZU, Jun ISHII, Izumi WASHITANI, Kenji OMASA
2011 Journal of Agricultural Meteorology  
The aim of this study was to map the probability of the establishment of this invasive grass in the shore of the Kinu River using airborne hyperspectral imagery.  ...  No available variable of original reflectance data was selected, but two bands of MNF were selected in the regression analysis.  ...  Muranaka of the Graduate School of Agricultural and Life Sciences, The University of Tokyo for his kind help during the field surveys.  ... 
doi:10.2480/agrmet.67.2.1 fatcat:c2lupwh7l5c45mbt7giwsely7e

A Low-Rate Video Approach to Hyperspectral Imaging of Dynamic Scenes

Charles Bachmann, Rehman Eon, Christopher Lapszynski, Gregory Badura, Anthony Vodacek, Matthew Hoffman, Donald Mckeown, Robert Kremens, Michael Richardson, Timothy Bauch, Mark Foote
2018 Journal of Imaging  
, 16 bit dynamic range, and 1600 × 300 spatial dimensions every second.  ...  Imaging near the shoreline in a coastal setting, we provide an example of hyperspectral imagery time series acquired during a field experiment in July 2017 with our integrated system, which produced hyperspectral  ...  In order to meet objectives (5) and (c) above, the imaging system that we selected had 16-bit dynamic range.  ... 
doi:10.3390/jimaging5010006 pmid:34470179 fatcat:7skikzzsrrapfbabhl6cx6ls64

FUSION OF HYPERSPECTRAL, MULTISPECTRAL, COLOR AND 3D POINT CLOUD INFORMATION FOR THE SEMANTIC INTERPRETATION OF URBAN ENVIRONMENTS

M. Weinmann, M. Weinmann
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
For the hyperspectral data, we involve techniques for dimensionality reduction and feature selection as well as a transformation to multispectral Sentinel-2-like data of the same spatial resolution.  ...  For the RGB color imagery, these are achieved via color invariants, normalization procedures or specific assumptions about the scene.  ...  CFS-based Band Selection from Hyperspectral Data: We define a feature set S HSI,CFS by focusing on band subset selection for which we apply Correlation-based Feature Selection (CFS) (Hall, 1999) , i.e  ... 
doi:10.5194/isprs-archives-xlii-2-w13-1899-2019 fatcat:3xq3myk2jng4la36z24q6ssgu4

Evaluation of Dimensional Reduction Methods on Urban Vegegation Classification Performance Using Hyperspectral Data

Brabant C, Alvarez-Vanhard E, Morin G, Thanh Nguyen K, Laribi A, Houet T
2018 IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium  
Evaluation of dimensional reduction methods on urban vegetation classification performance using hyperspectral data.  ...  Methodological approach The purpose of the hyperspectral images dimensional reduction is to select or extract an optimal subset from spectral bands that are relevant for the issue at stake.  ...  Results from Hypxim datasets will also be compared with those computed from Hyspec 2m data (492 spectral bands) and simulated Sentinel-2 imageries.  ... 
doi:10.1109/igarss.2018.8517410 dblp:conf/igarss/BrabantAMNLH18 fatcat:es3bzup2cjhu7ndwmfwtsipt5m

Mapping potential habitats of threatened plant species in a moist tall grassland using hyperspectral imagery

Jun Ishii, Shan Lu, Syo Funakoshi, Yo Shimizu, Kenji Omasa, Izumi Washitani
2009 Biodiversity and Conservation  
Linear regression models based on hyperspectral imagery band data had good accuracy in estimating P. australis and M. sacchariflorus shoot densities (adjusted R 2 = 0.686 and 0.708, respectively).  ...  We examined the capability of hyperspectral imagery to map habitat types of under-storey plants in a moist tall grassland dominated by Phragmites australis and Miscanthus sacchariflorus, using hyperspectral  ...  Masumi Ohwada for field assistance and advice on data analyses. We also thank two anonymous reviewers for valuable comments on an earlier version of the manuscript.  ... 
doi:10.1007/s10531-009-9605-7 fatcat:xhqoiii6cfdyzgpebx45goge74

Analysis of HYDICE data for information fusion in cartographic feature extraction

S.J. Ford, J.C. McGlone, S.D. Cochran, J.A. Shufelt, W.A. Harvey, D.M. McKeown
1998 IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174)  
Late in 1995 we organized a hyperspectral data acquisition using the Naval Research Laboratory's Hyperspectral Digital Imagery Collection Experiment sensor system over Fort Hood, Texas.  ...  This paper describes current quantitative classification results for man-made and natural materials using 14 surface material classes over selected test areas within Fort Hood.  ...  imagery and spectral reflectance measurements to calculate band gain and offset coefficients for each flightline.  ... 
doi:10.1109/igarss.1998.702324 fatcat:olp2he4hgbcw3dxqvdqsrw7y3m

Spatio-temporal patterns of chlorophyll fluorescence and physiological and structural indices acquired from hyperspectral imagery as compared with carbon fluxes measured with eddy covariance

P.J. Zarco-Tejada, A. Morales, L. Testi, F.J. Villalobos
2013 Remote Sensing of Environment  
A total of seven flights between summer and autumn were conducted with a hyperspectral camera that captured 30 cm resolution imagery and 260 spectral bands in the 400-900 nm region.  ...  These indicators are required for GPP monitoring when the vegetation dynamics are not captured by remote sensing structural indices.  ...  Regional Government of Andalusia for project P08-AGR-04202.  ... 
doi:10.1016/j.rse.2013.02.003 fatcat:dc2oyxynwfe2vnkipbihmnhb7u

A FULLY AUTOMATED AND FAST APPROACH FOR CANOPY COVER ESTIMATION USING SUPER HIGH-RESOLUTION REMOTE SENSING IMAGERY

M. Maimaitijiang, V. Sagan, S. Bhadra, C. Nguyen, T. C. Mockler, N. Shakoor
2021 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The proposed method was applied to high-resolution hyperspectral and multispectral imagery collected from gantry-based scanner and Unmanned Aerial Vehicle (UAV) platforms to estimate canopy cover.  ...  The results show that: the rule-based method demonstrated promising classification accuracies that are comparable to SVM and RF for both hyperspectral and multispectral datasets.  ...  selected testing samples (about 3,000 samples for each dataset).  ... 
doi:10.5194/isprs-annals-v-3-2021-219-2021 fatcat:kalfu3fzpnfnhnsxyuxbuikmsi

Urban land cover classification using hyperspectral data

G. Hegde, J. Mohammed Ahamed, R. Hebbar, U. Raj
2014 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The threshold Eigen value of 1.76 in VNIR region and 1.68 in the SWIR region was used for selection of 145 stable bands. Advanced per pixel classifiers <i>viz.  ...  Future research is focused on generating hyperspectral library for different urban features.  ...  Figure-3: MNF bands of VNIR region The hyperspectral profile for seven major urban land cover classes was generated to analyze the class separability and selection of bands that are best suitable for improved  ... 
doi:10.5194/isprsarchives-xl-8-751-2014 fatcat:2vll4lvndne5pdckx3dowus45u

Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood Maps

Burak Uzkent, Aneesh Rangnekar, Matthew J. Hoffman
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
The key idea is that our adaptive fusion method can combine likelihood maps from multiple bands of hyperspectral imagery into one single more distinctive representation increasing the margin between mean  ...  detection part of a tracking system and remove the necessity to build any offline classifiers and tune large amount of hyperparameters, instead learning a generative target model in an online manner for  ...  Overall, we obtain two images per frame -a wide FOV panchromatic imagery that is used for image registration and a narrow FOV hyperspectral imagery that is used for vehicle detection and tracking.  ... 
doi:10.1109/cvprw.2017.35 dblp:conf/cvpr/UzkentRH17 fatcat:qha2nwqgs5flzle7prloyvb2im
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