Field of Particle Filters Image Inpainting

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Standard

Field of Particle Filters Image Inpainting. / Cuzol, Anne; Pedersen, Kim Steenstrup; Nielsen, Mads.

I: Journal of Mathematical Imaging and Vision, Bind 31, Nr. 2-3, 2008, s. 147-156.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Cuzol, A, Pedersen, KS & Nielsen, M 2008, 'Field of Particle Filters Image Inpainting', Journal of Mathematical Imaging and Vision, bind 31, nr. 2-3, s. 147-156. https://doi.org/10.1007/s10851-008-0072-7

APA

Cuzol, A., Pedersen, K. S., & Nielsen, M. (2008). Field of Particle Filters Image Inpainting. Journal of Mathematical Imaging and Vision, 31(2-3), 147-156. https://doi.org/10.1007/s10851-008-0072-7

Vancouver

Cuzol A, Pedersen KS, Nielsen M. Field of Particle Filters Image Inpainting. Journal of Mathematical Imaging and Vision. 2008;31(2-3):147-156. https://doi.org/10.1007/s10851-008-0072-7

Author

Cuzol, Anne ; Pedersen, Kim Steenstrup ; Nielsen, Mads. / Field of Particle Filters Image Inpainting. I: Journal of Mathematical Imaging and Vision. 2008 ; Bind 31, Nr. 2-3. s. 147-156.

Bibtex

@article{da9c0030a01f11dd86a6000ea68e967b,
title = "Field of Particle Filters Image Inpainting",
abstract = "We present a novel algorithm for solving the imageinpainting problem based on a field of locally interactingparticle filters. Image inpainting, also known as imagecompletion, is concerned with the problem of filling imageregions with new visually plausible data. In order to avoidthe difficulty of solving the problem globally for the regionto be inpainted, we introduce a field of local particlefilters. The states of the particle filters are image patches.Global consistency is enforced by a Markov random fieldimage model which connects neighbouring particle filters.The benefit of using locally interacting particle filters is thatseveral competing hypotheses on inpainting solutions arekept active, allowing the method to provide globally consistentsolutions on problems where other local methods mayfail. We provide examples of applications of the developedmethod.Keywords: Inpainting · Image completion · Hole filling ·Particle filter · Markov random field",
keywords = "Faculty of Science, Inpainting, Image completion, Hole filling, Particle filter, Markov random field",
author = "Anne Cuzol and Pedersen, {Kim Steenstrup} and Mads Nielsen",
year = "2008",
doi = "10.1007/s10851-008-0072-7",
language = "English",
volume = "31",
pages = "147--156",
journal = "Journal of Mathematical Imaging and Vision",
issn = "0924-9907",
publisher = "Springer",
number = "2-3",

}

RIS

TY - JOUR

T1 - Field of Particle Filters Image Inpainting

AU - Cuzol, Anne

AU - Pedersen, Kim Steenstrup

AU - Nielsen, Mads

PY - 2008

Y1 - 2008

N2 - We present a novel algorithm for solving the imageinpainting problem based on a field of locally interactingparticle filters. Image inpainting, also known as imagecompletion, is concerned with the problem of filling imageregions with new visually plausible data. In order to avoidthe difficulty of solving the problem globally for the regionto be inpainted, we introduce a field of local particlefilters. The states of the particle filters are image patches.Global consistency is enforced by a Markov random fieldimage model which connects neighbouring particle filters.The benefit of using locally interacting particle filters is thatseveral competing hypotheses on inpainting solutions arekept active, allowing the method to provide globally consistentsolutions on problems where other local methods mayfail. We provide examples of applications of the developedmethod.Keywords: Inpainting · Image completion · Hole filling ·Particle filter · Markov random field

AB - We present a novel algorithm for solving the imageinpainting problem based on a field of locally interactingparticle filters. Image inpainting, also known as imagecompletion, is concerned with the problem of filling imageregions with new visually plausible data. In order to avoidthe difficulty of solving the problem globally for the regionto be inpainted, we introduce a field of local particlefilters. The states of the particle filters are image patches.Global consistency is enforced by a Markov random fieldimage model which connects neighbouring particle filters.The benefit of using locally interacting particle filters is thatseveral competing hypotheses on inpainting solutions arekept active, allowing the method to provide globally consistentsolutions on problems where other local methods mayfail. We provide examples of applications of the developedmethod.Keywords: Inpainting · Image completion · Hole filling ·Particle filter · Markov random field

KW - Faculty of Science

KW - Inpainting

KW - Image completion

KW - Hole filling

KW - Particle filter

KW - Markov random field

U2 - 10.1007/s10851-008-0072-7

DO - 10.1007/s10851-008-0072-7

M3 - Journal article

VL - 31

SP - 147

EP - 156

JO - Journal of Mathematical Imaging and Vision

JF - Journal of Mathematical Imaging and Vision

SN - 0924-9907

IS - 2-3

ER -

ID: 6746213