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Introduction to Variational Models in Image Processing
Introduction to Variational Models in Image Processingopenaire +1 more source
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Variational Bayesian image processing on stochastic factor graphs
2008 15th IEEE International Conference on Image Processing, 2008In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represent image patches and their clustering relationship respectively. Unlike previous probabilistic graphical models, we model the structure of FGs by a latent variable, which gives
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Combined First and Second Order Variational Approaches for Image Processing
Deutsche Mathematiker Vereinigung Jahresbericht, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gabriele Steidl
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IEEE Transactions on Image Processing, 1998 This paper examines the relationship between wavelet-based image processing algorithms and variational problems. Algorithms are derived as exact or approximate minimizers of variational problems; in particular, we show that wavelet shrinkage can be ...
Antonin Chambolle +2 more
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Matrix-variate variational auto-encoder with applications to image process
Journal of Visual Communication and Image Representation, 2020Abstract Variational Auto-Encoder (VAE) is an important probabilistic technology to model 1D vectorial data. However, when applying VAE model to 2D image, vectorization is necessary. Vectorization process may lead to dimension curse and lose valuable spatial information.
Jinghua Li +6 more
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On a Variational Problem from Image Processing
2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
David, Guy, Semmes, Stephen
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Total Variation Processing of Images with Poisson Statistics
2009This paper deals with denoising of density images with bad Poisson statistics (low count rates), where the reconstruction of the major structures seems the only reasonable task. Obtaining the structures with sharp edges can also be a prerequisite for further processing, e.g. segmentation of objects.
Alex Sawatzky +3 more
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Variational Methods in Image Processing
2018A short review is given on the rationale for using cost functions and optimization methods for modeling image processing and computer vision problems. Classical examples of various costs and functionals are given, illustrating this highly effective algorithmic approach. We examine different mathematical models Sects.
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Variational PDE models in image processing.
2003Summary: How can one restore a damaged picture? The authors discuss some recent applications of partial differential equations to such problems of image manipulation.
Chan, Tony F. +2 more
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