All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

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

The result's identifiers

  • 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>

Alternative languages

  • 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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • 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)

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • 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

  • UT code for WoS article

    000543397000207

  • EID of the result in the Scopus database

    2-s2.0-85086448215