Assessing Cloud Segmentation in the Chromacity Diagram of All-Sky Images

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00341648" target="_blank" >RIV/68407700:21230/20:00341648 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.3390/rs12111902" target="_blank" >https://doi.org/10.3390/rs12111902</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/rs12111902" target="_blank" >10.3390/rs12111902</a>

Result language

angličtina

Original language name

Assessing Cloud Segmentation in the Chromacity Diagram of All-Sky Images

Original language description

All-sky imaging systems are currently very popular. They are used in ground-based meteorological stations and as a crucial part of the weather monitors for autonomous robotic telescopes. Data from all-sky imaging cameras provide important information for controlling meteorological stations and telescopes, and they have specific characteristics different from widely-used imaging systems. A particularly promising and useful application of all-sky cameras is for remote sensing of cloud cover. Post-processing of the image data obtained from all-sky imaging cameras for automatic cloud detection and for cloud classification is a very demanding task. Accurate and rapid cloud detection can provide a good way to forecast weather events such as torrential rainfalls. However, the algorithms that are used must be specifically calibrated on data from the all-sky camera in order to set up an automatic cloud detection system. This paper presents an assessment of a modified k-means++ color-based segmentation algorithm specifically adjusted to the WILLIAM (WIde-field aLL-sky Image Analyzing Monitoring system) ground-based remote all-sky imaging system for cloud detection. The segmentation method is assessed in two different color-spaces (L*a*b and XYZ). Moreover, the proposed algorithm is tested on our public WMD database (WILLIAM Meteo Database) of annotated all-sky image data, which was created specifically for testing purposes. The WMD database is available for public use. In this paper, we present a comparison of selected color-spaces and assess their suitability for the cloud color segmentation based on all-sky images. In addition, we investigate the distribution of the segmented cloud phenomena present on the all-sky images based on the color-spaces channels. In the last part of this work, we propose and discuss the possible exploitation of the color-based k-means++ segmentation method as a preprocessing step towards cloud classification in all-sky images.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20201 - Electrical and electronic engineering

Project

<a href="/en/project/GA20-10907S" target="_blank" >GA20-10907S: Meteor clusters: An evidence for fragmentation of meteoroids in interplanetary space</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Remote sensing

ISSN

2072-4292

e-ISSN

—

Volume of the periodical

12

Issue of the periodical within the volume

11

Country of publishing house

CH - SWITZERLAND

Number of pages

13

Pages from-to

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UT code for WoS article

000543397000207

EID of the result in the Scopus database

2-s2.0-85086448215