| dc.contributor.author | Nguyen, Mathieu | |
| dc.contributor.author | Thomas, Jean Baptiste | |
| dc.contributor.author | Farup, Ivar | |
| dc.date.accessioned | 2023-02-17T09:37:19Z | |
| dc.date.available | 2023-02-17T09:37:19Z | |
| dc.date.created | 2022-08-17T12:40:09Z | |
| dc.date.issued | 2022 | |
| dc.identifier.issn | 1062-3701 | |
| dc.identifier.uri | https://hdl.handle.net/11250/3051851 | |
| dc.description.abstract | Sparkle from snow is a common phenomenon in Nature but not well studied in the literature. We perform a statistical study on digital snow images captured in-situ to analyze sparkle events by using contrast and density of sparkle spots descriptors. The method for measuring sparkles by Ferrero et al. is adapted, tested, and verified to the case of snow. The dataset is divided into three categories representing the type of snow acquired: dense snow, fresh snow, and old snow. Our analysis highlights the link between the sparkle of snow, the nature of snow and its grain structure. Sparkle could thus be a feature used for snow classification. | en_US |
| dc.description.abstract | Statistical Analysis of Sparkle in Snow Images | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Society for Imaging Science and Technology | en_US |
| dc.title | Statistical Analysis of Sparkle in Snow Images | en_US |
| dc.title.alternative | Statistical Analysis of Sparkle in Snow Images | en_US |
| dc.type | Peer reviewed | en_US |
| dc.type | Journal article | en_US |
| dc.description.version | acceptedVersion | en_US |
| dc.source.volume | 66 | en_US |
| dc.source.journal | Journal of Imaging Science and Technology | en_US |
| dc.source.issue | 5 | en_US |
| dc.identifier.doi | 10.2352/J.ImagingSci.Technol.2022.66.5.050404 | |
| dc.identifier.cristin | 2043798 | |
| cristin.ispublished | true | |
| cristin.fulltext | postprint | |
| cristin.fulltext | postprint | |
| cristin.qualitycode | 1 | |
