[PDF] Top 20 Unmixing dynamic PET images: combining spatial heterogeneity and non-Gaussian noise
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Unmixing dynamic PET images: combining spatial heterogeneity and non-Gaussian noise
... processing dynamic PET images is to identify the time-activity curves (TACs) of the pure tissues, along with their corresponding spatial ...as unmixing or factor analysis, is based on a ... Voir le document complet
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Unmixing dynamic PET images: combining spatial heterogeneity and non-Gaussian noise
... processing dynamic PET images is to identify the time-activity curves (TACs) of the pure tissues, along with their corresponding spatial ...as unmixing or factor analysis, is based on a ... Voir le document complet
7
Unmixing dynamic PET images for voxel-based kinetic component analysis
... analyze dynamic positron emission tomography (PET) images, various generic multivariate data analysis techniques have been considered in the literature, such as clustering, principal component ... Voir le document complet
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Unmixing dynamic PET images with a PALM algorithm
... NTRODUCTION Dynamic positron emission tomography (PET) is a medical imaging technique that provides time-activity curves (TACs) representing the variations over time of the concentration of a radiotracer in ... Voir le document complet
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Unmixing dynamic PET images with a PALM algorithm
... NTRODUCTION Dynamic positron emission tomography (PET) is a medical imaging technique that provides time-activity curves (TACs) representing the variations over time of the concentration of a radiotracer in ... Voir le document complet
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Non-linear unmixing of hyperspectral images using multiple-kernel self-organizing maps
... recent and rapid development of hyperspectral imaging technology, hyperspectral images have been widely used in various scientific fields, such as environmental mapping, risk prevention, urban planning, ... Voir le document complet
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Non-linear unmixing of hyperspectral images using multiple-kernel self-organizing maps
... hyperspectral images) to enrich the data similarity representations, (ii) it is an intermediate combination of data which means that the mixed pixel is preserved during the process without loss of information in ... Voir le document complet
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Conditional expected likelihood technique for compound Gaussian and Gaussian distributed noise mixtures
... support and/or SNR values, we observed strong departure from the clairvoyant lower ...a noise mixture does not exist in closed-form, and therefore availability of a CRB or of the exact ML estimator ... Voir le document complet
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Adaptive detection of a Gaussian signal in Gaussian noise
... attention, and the quasi totality of recent studies followed the lead of [4] and considered ↵ t p as deter- ministic ...a Gaussian signal in colored noise with unknown covariance matrix (while ... Voir le document complet
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Restoration of astrophysical images. The case of Poisson data with additive Gaussian noise
... m and of the astronomical ob- ject field u, then x(r, s) = u(r, s) + m(r, ...photons and the photosensitive material of the CCD creates photoelectrons in proportion to the number of photons plus extraneous ... Voir le document complet
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Nonlinear unmixing of hyperspectral images: Models and algorithms
... $ and 2) the constraints that have to be satisfied by the parameter vector ...FM and GBM, the authors propose to linearize the objective criterion via a first-order Taylor series expansion of { ( ) ... Voir le document complet
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Nonlinear unmixing of hyperspectral images: Models and algorithms
... approaches and physical models have the potential to greatly improve nonlinear unmixing ...dispersion, and beam interaction depth, a physical model can guide the choice of sim- plified mathematical ... Voir le document complet
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Significant edges in the case of a non-stationary Gaussian noise
... a gaussian kernel of width σ = 2 (middle) and σ = 4 (see first row of Figure ...image and on the images obtained after Gaussian filtering with respective standard deviation σ = 2 ... Voir le document complet
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Modeling spatial and temporal variabilities in hyperspectral image unmixing
... (HS) images have received an increasing interest due to the significant spectral information they convey about the materials present in a given ...limited spatial resolution of hyperspectral sensors implies ... Voir le document complet
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Hyperspectral unmixing accounting for spatial correlations and endmember variability
... Ψ and C, accord- ing to their conditional distributions ...sampled and to the complexity of the conditional distributions, we use a CHMC algorithm with good mixing prop- erties ...C} and the MAP ... Voir le document complet
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LiDAR-driven spatial regularization for hyperspectral unmixing
... spectral unmixing. This paper proposes a general framework for spectral unmixing that in- corporates LiDAR data to inform the spatial regularization applied to the abundance ...validated and ... Voir le document complet
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Combining equilibrium logic and dynamic logic
... : Dynamic Logic of Propositional Assignments In this section we define syntax and semantics of dynamic logic of propositional as- signments ( DL - PA ) and state complexity ...valuation ... Voir le document complet
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Enhancing hyperspectral image unmixing with spatial correlations
... new unmixing strategy studied in this paper assumes that the hyperspectral image to be analyzed is partitioned into ho- mogeneous regions (or classes) in which the abundance vectors have the same first and ... Voir le document complet
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Combining equilibrium logic and dynamic logic
... We have only two atomic programs in the language, namely +p and −p. Each of them minimally updates an HT model, if this is possible: in a sense, the former ‘upgrades the truth of p’ while the latter ‘downgrades ... Voir le document complet
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LiDAR-driven spatial regularization for hyperspectral unmixing
... of spatial regulariza- tions consists in not properly preserving the edges between homogeneous areas, even when using total variation (TV)- like ...The spatial regularization for these pixels can be ... Voir le document complet
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