Displaying similar documents to “An efficient algorithm for adaptive total variation based image decomposition and restoration”

a functional analysis model for natural images permitting structured compression

Jacques Froment (2010)

ESAIM: Control, Optimisation and Calculus of Variations

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This paper describes a compact perceptual image model intended for morphological representation of the visual information contained in natural images. We explain why the total variation can be a criterion to split the information between the two main visual structures, which are the sketch and the microtextures. We deduce a morphological decomposition scheme, based on a segmentation where the borders of the regions correspond to the location of the topological singularities of a topographic...

A branch-and-price algorithm for the windy rural postman problem

Hasan Murat Afsar, Nicolas Jozefowiez, Pierre Lopez (2012)

RAIRO - Operations Research

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In this paper, we propose an exact solution method for the windy rural postman problem (WRPP). The motivation to study this problem comes from some real-life applications, such as garbage collecting in a predefined sector with hills, where the traversing or the servicing speed can change following the direction. We present a Dantzig-Wolfe decomposition and a branch-and-price algorithm to solve the WRPP. To the best of our knowledge, Dantzig-Wolfe decomposition has never been used to...

A well-posed multiscale regularization scheme for digital image denoising

V.B. Surya Prasath (2011)

International Journal of Applied Mathematics and Computer Science

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We propose an edge adaptive digital image denoising and restoration scheme based on space dependent regularization. Traditional gradient based schemes use an edge map computed from gradients alone to drive the regularization. This may lead to the oversmoothing of the input image, and noise along edges can be amplified. To avoid these drawbacks, we make use of a multiscale descriptor given by a contextual edge detector obtained from local variances. Using a smooth transition from the...

Warm-start cuts for Generalized Benders Decomposition

Jakub Kůdela, Pavel Popela (2017)

Kybernetika

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In this paper, we describe a decomposition algorithm suitable for two-stage convex stochastic programs known as Generalized Benders Decomposition. For this algorithm we propose a new reformulation that incorporates a lower bound cut that serves as a warm-start, decreasing the overall computation time. Additionally, we test the performance of the proposed reformulation on two modifications of the algorithm (bunching and multicut) using numerical examples. The numerical part is programmed...