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

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Article number	105896
Journal	Optics and Lasers in Engineering
Volume	127
DOIs	https://doi.org/10.1016/j.optlaseng.2019.105896
Publication status	Published - 1 Apr 2020
Externally published	Yes

Keywords

Color images
Digital image correlation
Uncertainty quantification

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10.1016/j.optlaseng.2019.105896

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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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AU - Hild, F.

AU - Roux, S.

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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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JO - Optics and Lasers in Engineering

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Optimal digital color image correlation

Abstract

Keywords

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