Results 11 to 20 of about 13,906,445 (282)
Variational PDE Models in Image Processing [PDF]
, 2002 Abstract : Image processing, a traditionally engineering field, has attracted the attention of many mathematicians during the past two decades. From the vision and cognitive science point of view, image processing is a basic tool used to reconstruct the relative order, geometry, topology, patterns, and dynamics of the 3-D world from 2-D images ...
Luminita Vese +2 more
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Variational Bayesian multinomial probit regression with Gaussian process priors [PDF]
, 2006 It is well known in the statistics literature that augmenting binary and polychotomous response models with Gaussian latent variables enables exact Bayesian analysis via Gibbs sampling from the parameter posterior.
Rogers, S., Girolami, M.
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Loopy belief propagation and probabilistic image processing [PDF]
, 2003 Estimation of hyperparameters by maximization of the marginal likelihood in probabilistic image processing is investigated by using the cluster variation method.
Inoue, J., Tanaka, K., Titterington, M.
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First Order Algorithms in Variational Image Processing [PDF]
, 2016 Variational methods in imaging are nowadays developing towards a quite universal and flexible tool, allowing for highly successful approaches on tasks like denoising, deblurring, inpainting, segmentation, super-resolution, disparity, and optical flow estimation.
Burger, Martin (Professor) +2 more
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Mathematics, 2023 A mammography provides a grayscale image of the breast. The main challenge of analyzing mammography images is to extract the region boundary of the breast abnormality for further analysis.
Noor Ain Syazwani Mohd Ghani +5 more
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Variational semi-blind sparse deconvolution with orthogonal kernel bases and its application to MRFM [PDF]
, 2014 We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known.
Se Un Parka +5 more
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IEEE Access, 2016 This paper discusses a novel conceptual formulation of the fractional-order Euler-Lagrange equation for the fractional-order variational method, which is based on the fractional-order extremum method. In particular, the reverse incremental optimal search
Yi-Fei Pu
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Variational Methods in Surface Parameterization [PDF]
, 2005 A surface parameterization is a function that maps coordinates in a 2-dimensional parameter space to points on a surface. This thesis investigates two kinds of parameterizations for surfaces that are disc-like in shape.
Litke, Nathan Jacob
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A Characterization of the Domain of Beta-Divergence and Its Connection to Bregman Variational Model
Entropy, 2017 In image and signal processing, the beta-divergence is well known as a similarity measure between two positive objects. However, it is unclear whether or not the distance-like structure of beta-divergence is preserved, if we extend the domain of the beta-
Hyenkyun Woo
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Euler's elastica and curvature based model for image restoration. [PDF]
PLoS ONE, 2018 Minimization functionals related to Euler's elastica energy has a broad range of applications in computer vision and image processing. This paper proposes a novel Euler's elastica and curvature-based variational model for image restoration corrupted with
Mushtaq Ahmad Khan +3 more
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