Optimal digital color image correlation

J. Curt; M. Capaldo; F. Hild; S. Roux

doi:10.1016/j.optlaseng.2019.105896

Optimal digital color image correlation

J. Curt
, M. Capaldo
, F. Hild
, S. Roux

Lamsid/EDF/R and D
ENS Paris-Saclay

Résultats de recherche: Contribution à un journal › Article › Revue par des pairs

21 Citations (Scopus)

Résumé

Within the context of Digital Image Correlation (DIC), the optimal treatment of color images is considered. The mathematical bses of a weighted 3-field image correlation are first introduced, which are relevant for RGB encoded images. In this framework, noise characterization methods are developed as noise properties dictate the best suited metric to compare images. Consistent ways to process an image from elementary Bayer matrices are derived. Last, a case study on uncertainty quantification is performed.

langue originale	Anglais
Numéro d'article	105896
journal	Optics and Lasers in Engineering
Volume	127
Les DOIs	https://doi.org/10.1016/j.optlaseng.2019.105896
état	Publié - 1 avr. 2020
Modification externe	Oui

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10.1016/j.optlaseng.2019.105896

Contient cette citation

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title = "Optimal digital color image correlation",

abstract = "Within the context of Digital Image Correlation (DIC), the optimal treatment of color images is considered. The mathematical bses of a weighted 3-field image correlation are first introduced, which are relevant for RGB encoded images. In this framework, noise characterization methods are developed as noise properties dictate the best suited metric to compare images. Consistent ways to process an image from elementary Bayer matrices are derived. Last, a case study on uncertainty quantification is performed.",

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AB - Within the context of Digital Image Correlation (DIC), the optimal treatment of color images is considered. The mathematical bses of a weighted 3-field image correlation are first introduced, which are relevant for RGB encoded images. In this framework, noise characterization methods are developed as noise properties dictate the best suited metric to compare images. Consistent ways to process an image from elementary Bayer matrices are derived. Last, a case study on uncertainty quantification is performed.

KW - Color images

KW - Digital image correlation

KW - Uncertainty quantification

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DO - 10.1016/j.optlaseng.2019.105896

M3 - Article

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Optimal digital color image correlation

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