Demosaic-free color detection for particle images

Abstract We propose a robust method to detect colors, positions, and sizes of particles on color particle images. The method is free of color artifacts originating from the demosaic process of Bayer raw images. We test the method using synthetic color particle images to quantitatively evaluate its performance and demonstrate its capacity for precise extraction of colors while refining particle positions at sub-sub-pixel level. We demonstrate the method’s applicability by applying it to different types of particle images from laboratory experiments of color particle tracking velocimetry and liquid crystal thermometry. The method standardizes color detection on particle images and promises the improvement in final performances of these color-utilizing measurements.

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Publication Details

Journal
Experiments in Fluids
Published
2025-02-07
DOI
https://doi.org/10.1007/s00348-025-03972-8
Citations
2
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
3.43

Funders

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article

Demosaic-free color detection for particle images

Daisuke Noto, Kazushige Yoda, Yuji Tasaka
2 citations
Experiments in Fluids
Remote Sensing in Agriculture
3.43
article

Demosaic-free color detection for particle images

Daisuke Noto, Kazushige Yoda, Yuji Tasaka
article en
2 citations

Abstract

Abstract We propose a robust method to detect colors, positions, and sizes of particles on color particle images. The method is free of color artifacts originating from the demosaic process of Bayer raw images. We test the method using synthetic color particle images to quantitatively evaluate its performance and demonstrate its capacity for precise extraction of colors while refining particle positions at sub-sub-pixel level. We demonstrate the method’s applicability by applying it to different types of particle images from laboratory experiments of color particle tracking velocimetry and liquid crystal thermometry. The method standardizes color detection on particle images and promises the improvement in final performances of these color-utilizing measurements.

Experiments in FluidsVol. 66(3)
Hokkaido University (JP), University of Pennsylvania (US)
Precursory Research for Embryonic Science and Technology
Openalex Percentile: Top 11%
Remote Sensing in Agriculture
3.43
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