Oriented Half Gaussian Kernels and Anisotropic Diffusion

Baptiste Magnier, Philippe Montesinos

2014

Abstract

Nonlinear PDEs (partial differential equations) offer a convenient formal framework for image regularization and are at the origin of several efficient algorithms. In this paper, we present a new approach which is based (i) on a set of half Gaussian kernel filters, and (ii) a nonlinear anisotropic PDE diffusion. On one hand, half Gaussian kernels provide oriented filters whose flexibility enables to detect edges with great accuracy. On the other hand, a nonlinear anisotropic diffusion scheme offers a means to smooth images while preserving fine structures or details, e.g. lines, corners and junctions. Based on the calculus of the gradient magnitude and two diffusion directions, we construct a diffusion control function able to achieve precise image regularization. Some quantified experimental results compared to existing PDEs approaches and a discussion about the parameterizing of the method are presented.

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Paper Citation


in Harvard Style

Magnier B. and Montesinos P. (2014). Oriented Half Gaussian Kernels and Anisotropic Diffusion . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 73-81. DOI: 10.5220/0004679500730081


in Bibtex Style

@conference{visapp14,
author={Baptiste Magnier and Philippe Montesinos},
title={Oriented Half Gaussian Kernels and Anisotropic Diffusion},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={73-81},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004679500730081},
isbn={978-989-758-003-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - Oriented Half Gaussian Kernels and Anisotropic Diffusion
SN - 978-989-758-003-1
AU - Magnier B.
AU - Montesinos P.
PY - 2014
SP - 73
EP - 81
DO - 10.5220/0004679500730081