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Relevant bibliographies by topics / Laplace Gaussian Filter

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Academic literature on the topic 'Laplace Gaussian Filter'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Laplace Gaussian Filter"

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Kleptsyna, M. L., A. Le Breton, and M. Viot. "New formulas concerning Laplace transforms of quadratic forms for general Gaussian sequences." Journal of Applied Mathematics and Stochastic Analysis 15, no. 4 (2002): 309–25. http://dx.doi.org/10.1155/s1048953302000266.

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Various methods to derive new formulas for the Laplace transforms of some quadratic forms of Gaussian sequences are discussed. In the general setting, an approach based on the resolution of an appropriate auxiliary filtering problem is developed; it leads to a formula in terms of the solutions of Volterra-type recursions describing characteristics of the corresponding optimal filter. In the case of Gauss-Markov sequences, where the previous equations reduce to ordinary forward recursive equations, an alternative approach prices another formula; it involves the solution of a backward recursive

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Waheed, M. El-Sayed, Mohamed-H. Mousa, and Mohamed-K. Hussein. "Blind Deconvolution of Sources in Fourier Space Based on Generalized Laplace Distribution." International Journal of System Dynamics Applications 2, no. 2 (2013): 55–65. http://dx.doi.org/10.4018/ijsda.2013040104.

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An approach to multi-channel blind de-convolution is developed, which uses an adaptive filter that performs blind source separation in the Fourier space. The approach keeps (during the learning process) the same permutation and provides appropriate scaling of components for all frequency bins in the frequency space. Experiments indicate that Generalized Laplace Distribution can be used effectively to blind de-convolution of convolution mixtures of sources in Fourier space compared to the conventional Laplacian and Gaussian function.

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Jiang, X., P. Cooper, and P. J. Scott. "Freeform surface filtering using the diffusion equation." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 467, no. 2127 (2010): 841–59. http://dx.doi.org/10.1098/rspa.2010.0307.

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The measurement of texture for geometric surfaces is well established for surfaces that are of a planar (Euclidean) nature. Gaussian filtering is the fundamental base for scale-limited surfaces used in surface texture, but cannot be applied to non-Euclidean surfaces without distortion of the results. A link exists between Gaussian filtering and solutions of the PDE that models linear isotropic diffusion. In particular, an analytical solution of this diffusion equation over a planar region at a time t is given by the continuous convolution of the initial distribution of the diffused quantity wi

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Chen, Ming. "Fractional-Order Adaptive P -Laplace Equation-Based Art Image Edge Detection." Advances in Mathematical Physics 2021 (August 31, 2021): 1–10. http://dx.doi.org/10.1155/2021/2337712.

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In recent years, with the rapid development of image processing research, the study of nonstandard images has gradually become a research hotspot, for example, fabric images, remote sensing images, and gear images. Some of the remote sensing images have a complex background and low illumination compared with standard images and are easy to be mixed with noise during acquisition; some of the fabric images have rich texture information, which adds difficulty to the related processing, and are also easy to be mixed with noise during acquisition. In this paper, we propose a fractional-order adapti

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Wang, Hao, and Kaiju Li. "Resistance of IID Noise in Differentially Private Schemes for Trajectory Publishing." Computer Journal 63, no. 4 (2019): 549–66. http://dx.doi.org/10.1093/comjnl/bxz097.

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Abstract Although analyzing and mining user’s trajectory data can provide outstanding benefit, data owners may not be willing to upload their trajectory data because of privacy concerns. Recently, differential privacy technology has achieved a good trade-off between data utility and privacy preserving by publishing noisy outputs, and relevant schemes have been proposed for trajectory release. However, we experimentally find that a relatively accurate estimate of the true data value can still be obtained from the noisy outputs by means of a posterior estimation. But there are no practical mecha

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"A filter with a guaranteed asymptotic performance." Proceedings of the Royal Society of London. Series A: Mathematical and Physical Sciences 441, no. 1911 (1993): 33–57. http://dx.doi.org/10.1098/rspa.1993.0047.

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In the case of low noise levels the optimal probability density function summarizing the available information about the state of a system can be accurately approximated by the product of a gaussian function and a linear function. The approximation preserves the ability to estimate to an accuracy of O ( λ -2 ) the expected value of any twice continuously differentiable function defined on the state space. The parameter λ depends on the noise level. If the noise level in the system is low then λ is large. A new filtering method based on this approximation is described. The approximating functio

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Wang, Xianghai, Wenya Zhang, Rui Li, and Ruoxi Song. "The UDWT image denoising method based on the PDE model of a convexity-preserving diffusion function." EURASIP Journal on Image and Video Processing 2019, no. 1 (2019). http://dx.doi.org/10.1186/s13640-019-0480-1.

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Abstract It is a great challenge to maintain details while suppressing and eliminating noise of the image. Considering the nonconvexity property of the diffusion function and the hypersensitivity of the Laplace operator to noise in the Y-K model, a fourth-order PDE image denoising model (Con_G&L model) is proposed in this paper. This model is constructed by a new convexity-preserving diffusion function which guarantees the corresponding energy functional has a globally unique minimum solution. At the same time, the Gaussian filter is combined with the Laplace operator in this model, and as

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Dissertations / Theses on the topic "Laplace Gaussian Filter"

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Castellanos, Lucia. "Statistical Models and Algorithms for Studying Hand and Finger Kinematics and their Neural Mechanisms." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/273.

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The primate hand, a biomechanical structure with over twenty kinematic degrees of freedom, has an elaborate anatomical architecture. Although the hand requires complex, coordinated neural control, it endows its owner with an astonishing range of dexterous finger movements. Despite a century of research, however, the neural mechanisms that enable finger and grasping movements in primates are largely unknown. In this thesis, we investigate statistical models of finger movement that can provide insights into the mechanics of the hand, and that can have applications in neural-motor prostheses, ena

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Neycenssac, Franck. "Segmentation d'images : intérêt d'un filtrage multi-échelle calculé par intégration du Laplacien d'une Gaussienne sur son écart-type." Toulouse 3, 1991. http://www.theses.fr/1991TOU30203.

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Les etudes sur la vision et la segmentation en traitement d'images numeriques trouvent un interet commun dans l'utilisation du laplacien d'une gaussienne. Le filtre lgfti, construit par integration de la transformee de fourier du laplacien d'une gaussienne dans l'espace des echelles, complete l'arsenal des filtrages du type laplacien. Le filtre lgfti offre des possibilites puissantes, car selon les bornes d'integration choisies on peut selectionner differemment les frequences utiles; il est donc plus adapte que le laplacien d'une gaussienne a la segmentation primitive. Nous avons montre qu'il

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Conference papers on the topic "Laplace Gaussian Filter"

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Mallick, Arijit, Sourya Roy, Sheli Sinha Chaudhuri, and Sangita Roy. "Optimization of Laplace of Gaussian (LoG) filter for enhanced edge detection: A new approach." In 2014 International Conference on Control, Instrumentation, Energy and Communication (CIEC). IEEE, 2014. http://dx.doi.org/10.1109/ciec.2014.6959172.

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Liu, Jianlei. "Two-dimensional anisotropic Gaussian-Laplace filter design for visibility distance estimation under foggy weather." In 2016 35th Chinese Control Conference (CCC). IEEE, 2016. http://dx.doi.org/10.1109/chicc.2016.7553991.

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Galtier, Thomas, Sayan Gupta, and Igor Rychlik. "Approximation of Crossing Intensities for Non Linear Responses Subjected to Non Gaussian Loadings." In ASME 2010 29th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2010. http://dx.doi.org/10.1115/omae2010-20114.

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Crossing intensity constitute an important response characteristic for randomly vibrating structures, especially if one is interested in estimating the risk against failures. This paper focusses on developing approximations by which estimates of the crossing intensities for response of marine structures can be obtained in a computationally efficient manner, when the loads are modeled as a special class of non-Gaussian processes, namely as LMA processes. Ocean waves exhibit considerable non-Gaussianity as marked by their skewed marginal distributions and heavy tails. Here, a new class of proces

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