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ACM SIGGRAPH ASIA 2009 Sketches, 2009
Most of the real world scenes have a very high dynamic range. However the common capture and display devices can handle only a limited dynamic range. General approach to solve this problem is to use multi-exposure images and composite them in the irradiance domain to get a High Dynamic Range (HDR) image [Reinhard et al. 2005].
Shanmuganathan Raman, Subhasis Chaudhuri
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Most of the real world scenes have a very high dynamic range. However the common capture and display devices can handle only a limited dynamic range. General approach to solve this problem is to use multi-exposure images and composite them in the irradiance domain to get a High Dynamic Range (HDR) image [Reinhard et al. 2005].
Shanmuganathan Raman, Subhasis Chaudhuri
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International Journal of Mathematics, 1995
Some important properties of Poisson groupoids are discussed. In particular, we obtain a useful formula for the Poisson tensor of an arbitrary Poisson groupoid, which generalizes the well-known multiplicativity condition for Poisson groups. Morphisms between Poisson groupoids and between Lie bialgebroids are also discussed.
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Some important properties of Poisson groupoids are discussed. In particular, we obtain a useful formula for the Poisson tensor of an arbitrary Poisson groupoid, which generalizes the well-known multiplicativity condition for Poisson groups. Morphisms between Poisson groupoids and between Lie bialgebroids are also discussed.
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Exact results on Poisson noise, Poisson flights, and Poisson fluctuations
Journal of Mathematical Physics, 2021We study non-Markovian stochastic differential equations with additive noise characterized by a Poisson point process with arbitrary pulse shapes and exponentially distributed intensities. Specifically, analytic results concerning transitions between different correlation regimes and the long-time asymptotic probability distribution functions are shown
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The Poisson Process, Compound Poisson Process, and Poisson Random Field
2021Poisson processes broadly refer to stochastic processes that are the result of counting occurrences of some random phenomena (points) in time or space such that occurrences of points in disjoint regions are statistically independent, and counts of two or more occurrences in an infinitesimally small region are negligible.
Rabi Bhattacharya, Edward C. Waymire
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Poisson point and Poisson processes
2017This chapter starts with a general description of Poisson point processes. These processes are defined from four natural axioms describing the spatial distribution of so-called Poisson points scattered homogeneously in a random manner across the d-dimensional Euclidean space.
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Poisson Numbers and Poisson Distributions in Subset Surprisology
Annals of Combinatorics, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dress, Andreas W. M. +3 more
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Computing in Science & Engineering, 2001
Scientists and engineers often use Poisson's probability distribution to characterize the statistics of rare events whose average number is small. Using it correctly is crucial if we are to validate claims of discovery of new phenomena, such as a new fundamental particle (few candidate collision events among millions), a remote galaxy (few photons in ...
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Scientists and engineers often use Poisson's probability distribution to characterize the statistics of rare events whose average number is small. Using it correctly is crucial if we are to validate claims of discovery of new phenomena, such as a new fundamental particle (few candidate collision events among millions), a remote galaxy (few photons in ...
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Dirac structures and poisson reductions on poisson groupoids
Reports on Mathematical Physics, 2004The author characterizes Dirac structures on Poissob actions in terms of their characteristic pairs. Using the characteristic pairs introduced by Liu, the author gives a characterization of Dirac structures and provides new proofs of the properties concerning pullback Dirac structures on the actions of Poisson groupoids.
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