Title:
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Linear multiscale analysis of similarities between images on Riemannian manifolds: practical formula and affine covariant metrics
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Author:
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Fedorov, Vadim; Arias Martínez, Pablo; Sadek, Rida; Facciolo Furlan, Gabriele; Ballester, Coloma
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Abstract:
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In this paper we study the problem of comparing two patches of images defined on Riemannian/nmanifolds which in turn can be defined by each image domain with a suitable metric depending on/nthe image. For that we single out one particular instance of a set of models defining image similarities/nthat was earlier studied in [C. Ballester et al., Multiscale Model. Simul., 12 (2014), pp. 616–649],/nusing an axiomatic approach that extended the classical Alvarez–Guichard–Lions–Morel work to the ´/nnonlocal case. Namely, we study a linear model to compare patches defined on two images in RN/nendowed with some metric. Besides its genericity, this linear model is selected by its computational/nfeasibility since it can be approximated leading to an algorithm that has the complexity of the/nusual patch comparison using a weighted Euclidean distance. Moreover, we propose and study some/nintrinsic metrics which we define in terms of affine covariant structure tensors and we discuss their/nproperties. These tensors are defined for any point in the image and are intrinsically endowed with/naffine covariant neighborhoods. We also discuss the effect of discretization over the affine covariance/nproperties of the tensors. We illustrate our theoretical results with numerical experiments. |
Abstract:
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The research of these authors was partially supported by MICINN project MTM2012-30772, by the ERC Advanced Grant INPAINTING (grant agreement 319899), and by GRC reference 2014 SGR 1301, Generalitat de Catalunya. |
Subject(s):
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-Multiscale analysis -Similarity measures -Degenerate parabolic equations -Structure tensors -Affine invariance |
Rights:
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© 2015 Society for Industrial and Applied Mathematics
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Document type:
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Article Article - Published version |
Published by:
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SIAM (Society for Industrial and Applied Mathematics)
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