Results 1 to 10 of about 2,330,920 (308)
First order algorithms in variational image processing [PDF]
arXiv.org, 2014 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 ...
Burger, Martin +2 more
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Variational Anisotropic Gradient-Domain Image Processing [PDF]
Journal of Imaging, 2021 Gradient-domain image processing is a technique where, instead of operating directly on the image pixel values, the gradient of the image is computed and processed. The resulting image is obtained by reintegrating the processed gradient. This is normally
Ivar Farup
doaj +3 more sources
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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Introduction to variational image-processing models and applications [PDF]
International Journal of Computer Mathematics, 2013 Variational image-processing models offer high-quality processing capabilities for imaging. They have been widely developed and used in the last two decades, enriching the fields of mathematics as well as information science. Mathematically, several tools are needed: energy optimization, regularization, partial differential equations, level set ...
Ke Chen
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Some variational problems from image processing [PDF]
, 2009 "Vegeu el resum a l'inici del document del fitxer adjunt"
Garnett, John B. +3 more
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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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Patch-based methods for variational image processing problems
, 2013 Image Processing problems are notoriously difficult. To name a few of these difficulties, they are usually ill-posed, involve a huge number of unknowns (from one to several per pixel!), and images cannot be considered as the linear superposition of a few physical sources as they contain many different scales and non-linearities.
E. d'Angelo
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Variational Methods in Image Processing
, 2015 Luminita A. Vese, Carole Le Guyader
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Whiteness-based parameter selection for Poisson data in variational image processing [PDF]
Applied Mathematical Modelling, 2022 We propose a novel automatic parameter selection strategy for variational imaging problems under Poisson noise corruption. The selection of a suitable regularization parameter, whose value is crucial in order to achieve high quality reconstructions, is ...
F. Bevilacqua +3 more
semanticscholar +1 more source
Variational Deep Image Restoration [PDF]
IEEE Transactions on Image Processing, 2022 This paper presents a new variational inference framework for image restoration and a convolutional neural network (CNN) structure that can solve the restoration problems described by the proposed framework.
Jae Woong Soh, N. Cho
semanticscholar +1 more source