Colour transformations and K-means segmentation for automatic cloud detection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00231193" target="_blank" >RIV/68407700:21230/15:00231193 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.schweizerbart.de/papers/metz/detail/24/85014/Colour_transformations_and_K_means_segmentation_for_automatic_cloud_detection" target="_blank" >http://www.schweizerbart.de/papers/metz/detail/24/85014/Colour_transformations_and_K_means_segmentation_for_automatic_cloud_detection</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1127/metz/2015/0656" target="_blank" >10.1127/metz/2015/0656</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Colour transformations and K-means segmentation for automatic cloud detection

Popis výsledku v původním jazyce

The main aim of this work is to find simple criteria for automatic recognition of several meteorological phenomena using optical digital sensors (e.g., Wide-Field cameras, automatic DSLR cameras or robotic telescopes). The output of those sensors is commonly represented in RGB channels containing information about both colour and luminosity even when normalised. Transformation into other colour spaces (e.g., CIE 1931 xyz, CIE L*a*b*, YCbCr) can separate colour from luminosity, which is especially usefulin the image processing of automatic cloud boundary recognition. Different colour transformations provide different sectorization of cloudy images. Hence, the analysed meteorological phenomena (cloud types, clear sky) project differently into the colourdiagrams of each international colour systems. In such diagrams, statistical tools can be applied in search of criteria which could determine clear sky from a covered one and possibly even perform a meteorological classification of cloud

Název v anglickém jazyce

Colour transformations and K-means segmentation for automatic cloud detection

Popis výsledku anglicky

The main aim of this work is to find simple criteria for automatic recognition of several meteorological phenomena using optical digital sensors (e.g., Wide-Field cameras, automatic DSLR cameras or robotic telescopes). The output of those sensors is commonly represented in RGB channels containing information about both colour and luminosity even when normalised. Transformation into other colour spaces (e.g., CIE 1931 xyz, CIE L*a*b*, YCbCr) can separate colour from luminosity, which is especially usefulin the image processing of automatic cloud boundary recognition. Different colour transformations provide different sectorization of cloudy images. Hence, the analysed meteorological phenomena (cloud types, clear sky) project differently into the colourdiagrams of each international colour systems. In such diagrams, statistical tools can be applied in search of criteria which could determine clear sky from a covered one and possibly even perform a meteorological classification of cloud

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

<a href="/cs/project/GA14-25251S" target="_blank" >GA14-25251S: Nelineární obrazové systémy s prostorově variantní bodovou rozptylovou funkcí</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Meteorologische Zeitschrift

ISSN

0941-2948

e-ISSN

—

Svazek periodika

24

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

7

Strana od-do

503-509

Kód UT WoS článku

000363428300004

EID výsledku v databázi Scopus

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