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A Unified Framework for Multi-Sensor HDR Video Reconstruction
[article]
2013
arXiv
pre-print
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One of the most successful approaches to modern high quality HDR-video capture is to use camera setups with multiple sensors imaging the scene through a common optical system. ...
Our framework includes a camera noise model adapted to HDR video and an algorithm for spatially adaptive HDR reconstruction based on fitting of local polynomial approximations to observed sensor data. ...
In this work we consider the Gaussian window function for its simplicity and widespread use. The 2 × 2 smoothing matrix, H, affects the shape of the Gaussian. ...
arXiv:1308.4908v1
fatcat:5hkpbtfnsbfhvdj6ltapjvawom
Unsupervised Change Detection in Multi-temporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network
[article]
2019
arXiv
pre-print
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In this paper, a novel unsupervised model called kernel principal component analysis (KPCA) convolution is proposed for extracting representative features from multi-temporal VHR images. ...
With the development of Earth observation technology, very-high-resolution (VHR) image has become an important data source of change detection. ...
MAD is a CD method based on the canonical correlation analysis (CCA), which is first proposed in [27] . ...
arXiv:1912.08628v1
fatcat:ktvof2jbu5fbxovcpckyosyt5i
Supervised and Semi-Supervised Multi-View Canonical Correlation Analysis Ensemble for Heterogeneous Domain Adaptation in Remote Sensing Image Classification
2017
Remote Sensing
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a geodesic Gaussian flow kernel based support vector machine (GFKSVM) in the context of hyperspectral image classification, which adopts several unsupervised linear and nonlinear subspace feature transfer ...
As monitoring requires multi-temporal images, radiometric differences, atmospheric and illumination conditions, seasonal variations, and variable acquisition geometries can affect supervised techniques ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs9040337
fatcat:cq27i7bnzfdk7ot2emgnfgmwpi
Review ArticleDigital change detection methods in ecosystem monitoring: a review
2004
International Journal of Remote Sensing
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Change detection between pairs of images (bi-temporal) as well as between time profiles of imagery derived indicators (temporal trajectories), and, where relevant, the appropriate choices for digital imagery ...
Techniques based on multi-temporal, multi-spectral, satellite-sensoracquired data have demonstrated potential as a means to detect, identify, map and monitor ecosystem changes, irrespective of their causal ...
Nielsen et al. (1998) proposed the multivariate alteration detection or MAD, which is an extension of the traditional canonical correlations analysis and is invariant to linear scaling of the input data ...
doi:10.1080/0143116031000101675
fatcat:bxqzwlf4trfdxk74hs5b5dyui4
2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57
2019
IEEE Transactions on Geoscience and Remote Sensing
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and Hanssen, R.F., Incorporating Temporary Coherent Li, X., Yeo, T.S., Yang, Y., Chi, C., Zuo, F., Hu, X., and Pi, Y., Refo-cusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging ...
Hu, C., Zhang, B., Dong, X., and Li, Y., Geosynchronous SAR Tomography: Theory and First Experimental Verification Using Beidou IGSO Satellite; TGRS Sept. 2019 6591-6607 Hu, F., Wu, J., Chang, L., ...
., +, TGRS Nov. 2019 8719-8731
Cross-Domain Collaborative Learning via Cluster Canonical Correlation
Analysis and Random Walker for Hyperspectral Image Classification. ...
doi:10.1109/tgrs.2020.2967201
fatcat:kpfxoidv5bgcfo36zfsnxe4aj4
Hyperspectral Remote Sensing Data Analysis and Future Challenges
2013
IEEE Geoscience and Remote Sensing Magazine
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Current sensors onboard airborne and spaceborne platforms cover large areas of the Earth surface with unprecedented spectral, spatial, and temporal resolutions. ...
The sources of difficulties are, namely, the high dimensionality and size of the hyperspectral data, the spectral mixing (linear and nonlinear), and the degradation mechanisms associated to the measurement ...
Linear kernels, radial-basis functions, polynomial, and physics-based kernels were proposed [61] . ...
doi:10.1109/mgrs.2013.2244672
fatcat:4tk7q6izd5hevhnrck36i5wkiy
2015 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 53
2015
IEEE Transactions on Geoscience and Remote Sensing
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., +, TGRS Aug. 2015 4472-4482 Linear Spectral Mixture Analysis via Multiple-Kernel Learning for Hyperspectral Image Classification. ...
., +, TGRS July 2015 3681-3693 Model-Based Fusion of Multi-and Hyperspectral Images Using PCA and Wavelets. ...
doi:10.1109/tgrs.2015.2513444
fatcat:zuklkpk4gjdxjegoym5oagotzq
Ultrasound image segmentation using local statistics with an adaptive scale selection
2012
2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)
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The scale is optimal in the sense that it gives the best trade-o between the bias and the variance of a Local Polynomial Approximation of the observed image conditional on the current segmentation. ...
More general experiments on real images also demonstrate the usefulness of our approach. ...
The speckle is a multiplicative noise, strongly correlated and more importantly, with non-Gaussian statistics. ...
doi:10.1109/isbi.2012.6235750
dblp:conf/isbi/YangB12
fatcat:dgu5vevcbbh7xjgz2q67owndam
Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art
2017
IEEE Geoscience and Remote Sensing Magazine
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Recent advances in airborne and spaceborne hyperspectral imaging technology have provided end users with rich spectral, spatial, and temporal information, which make a plethora of applications for the ...
analysis of large areas of the Earth surface feasible. ...
In addition, the authors would like to thank the National Center for Airborne Laser Mapping (NCALM) at the University of Houston for providing the CASI Houston data set, and the IEEE GRSS Image Analysis ...
doi:10.1109/mgrs.2017.2762087
fatcat:6ezzye7yyvacbouduqv2f2c7gi
Overview: Estimating and reporting uncertainties in remotely sensed atmospheric composition and temperature
2020
Atmospheric Measurement Techniques
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Many errors derive from approximations and simplifications used in real-world retrieval schemes, which are reviewed in this paper, along with related error estimation schemes. ...
Beyond this, it is of utmost importance to know the influence of any constraint and prior information on the solution. ...
of this term. 4 Normal distribution and Gaussian distribution are the same. ...
doi:10.5194/amt-13-4393-2020
fatcat:xrrrstul5vbxbbpwhrvkjzoo5a
Modeling & Analysis
2003
NeuroImage
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A suitable method of quantifying correlations in spatio-temporal data, and 2. ...
Tri-cubic interpolation was used while reslicing the images. (2) Expert quality control: Normalized PD images (n=527) were reviewed by an expert. ...
Images were normalized and segmented into gray and white matter and CSF [4]. ...
doi:10.1016/s1053-8119(05)70006-9
fatcat:zff2suxcofbxvetfrwfwcxi3zm
Computational light field display for correcting visual aberrations
2013
ACM SIGGRAPH 2013 Posters on - SIGGRAPH '13
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We analyze the image formation models; through the retinal light field projection, we find it is possible to compensate for the optical blurring on the target image by prefiltering with the inverse blur ...
Furthermore, higher order aberrations are not correctable with eyeglasses. ...
a radiometrically linear display. ...
doi:10.1145/2503385.2503430
dblp:conf/siggraph/HuangWBR13
fatcat:pjzzbcrdpjaafk57baz7hd7oca
Principles of appearance acquisition and representation
2008
ACM SIGGRAPH 2008 classes on - SIGGRAPH '08
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The radiometric calibration finally calibrates for the feeding fiber's irradiance and the spectral sensitivity of the camera sensor by measuring the diffusion kernel of a sample of skim milk using our ...
Notice that part of this term resembles a Gaussian. ...
Skin Trait Variance In order to detect correlations between reflectance parameters and the traits associated with each subject, we perform canonical correlation analysis (CCA). ...
doi:10.1145/1401132.1401234
dblp:conf/siggraph/WeyrichLLRZ08
fatcat:3mgaott37ngs5kdmvqmhhr7uzu
Principles of Appearance Acquisition and Representation
2007
Foundations and Trends in Computer Graphics and Vision
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The radiometric calibration finally calibrates for the feeding fiber's irradiance and the spectral sensitivity of the camera sensor by measuring the diffusion kernel of a sample of skim milk using our ...
Notice that part of this term resembles a Gaussian. ...
Skin Trait Variance In order to detect correlations between reflectance parameters and the traits associated with each subject, we perform canonical correlation analysis (CCA). ...
doi:10.1561/0600000022
fatcat:7dro6xcvz5hotdxmr7yvvkvr3y
Forest Leaf Mass per Area (LMA) through the Eye of Optical Remote Sensing: A Review and Future Outlook
2021
Remote Sensing
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The physiology and environmental factors that influence the spatial and temporal variation of LMA are presented. ...
The scope of scaling LMA using remote sensing systems at various scales, i.e., near ground (in situ), airborne, and spaceborne platforms is reviewed and discussed. ...
Acknowledgments: The authors appreciate comments and suggestions from the three anonymous reviewers that improved the quality of the manuscript. ...
doi:10.3390/rs13173352
fatcat:ddx6j4fvrbhprf2pchdeohlnji
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