Robust cloud estimation for GMS images considering the dynamic changes on VIS/IR data

Hiroshi Hiranaka; An Ngoc Van; Yoshimitsu Aoki

doi:10.1117/12.800066

Robust cloud estimation for GMS images considering the dynamic changes on VIS/IR data

Hiroshi Hiranaka, An Ngoc Van, Yoshimitsu Aoki

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper proposes a method that estimates the position of clouds from VIS images (visible), and IR images (infrared) of GMS (Geostationary Meteorological Satellite). In estimating the position of clouds, because the brightness value of land and sea is lower than cloud, and the brightness value of land and sea is continually varied by altitude of sun, the cloud area cannot be estimated by threshold processing. In this study, Variation character of brightness value is classified in each area, and the processing method of each area is proposed based on this variation character. In land area, there is correlation between brightness value of VIS and IR image if the area is not covered by cloud. Thus, the object domain is estimated cloud area using the correlation between them. In sea area, due to temperature is stable, cloud area is estimated by background subtraction method. This method was used to estimate and evaluated in the 202 GMS-5 images. The evaluated results shown that the proposed method is more accurate than the previous method, which estimated by threshold processing (Omi, 2003).

Original language	English
Title of host publication	Remote Sensing of Clouds and the Atmosphere XIII
DOIs	https://doi.org/10.1117/12.800066
Publication status	Published - 2008
Externally published	Yes
Event	Remote Sensing of Clouds and the Atmosphere XIII - Cardiff, Wales, United Kingdom Duration: 2008 Sept 15 → 2008 Sept 17

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	7107
ISSN (Print)	0277-786X

Other

Other	Remote Sensing of Clouds and the Atmosphere XIII
Country/Territory	United Kingdom
City	Cardiff, Wales
Period	08/9/15 → 08/9/17

Keywords

Area segmentation
Cloud area
GMS

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.800066

Cite this

Robust cloud estimation for GMS images considering the dynamic changes on VIS/IR data. / Hiranaka, Hiroshi; Van, An Ngoc; Aoki, Yoshimitsu.
Remote Sensing of Clouds and the Atmosphere XIII. 2008. 710702 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 7107).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hiranaka, H, Van, AN & Aoki, Y 2008, Robust cloud estimation for GMS images considering the dynamic changes on VIS/IR data. in Remote Sensing of Clouds and the Atmosphere XIII., 710702, Proceedings of SPIE - The International Society for Optical Engineering, vol. 7107, Remote Sensing of Clouds and the Atmosphere XIII, Cardiff, Wales, United Kingdom, 08/9/15. https://doi.org/10.1117/12.800066

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title = "Robust cloud estimation for GMS images considering the dynamic changes on VIS/IR data",

abstract = "This paper proposes a method that estimates the position of clouds from VIS images (visible), and IR images (infrared) of GMS (Geostationary Meteorological Satellite). In estimating the position of clouds, because the brightness value of land and sea is lower than cloud, and the brightness value of land and sea is continually varied by altitude of sun, the cloud area cannot be estimated by threshold processing. In this study, Variation character of brightness value is classified in each area, and the processing method of each area is proposed based on this variation character. In land area, there is correlation between brightness value of VIS and IR image if the area is not covered by cloud. Thus, the object domain is estimated cloud area using the correlation between them. In sea area, due to temperature is stable, cloud area is estimated by background subtraction method. This method was used to estimate and evaluated in the 202 GMS-5 images. The evaluated results shown that the proposed method is more accurate than the previous method, which estimated by threshold processing (Omi, 2003).",

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AU - Hiranaka, Hiroshi

AU - Van, An Ngoc

AU - Aoki, Yoshimitsu

PY - 2008

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N2 - This paper proposes a method that estimates the position of clouds from VIS images (visible), and IR images (infrared) of GMS (Geostationary Meteorological Satellite). In estimating the position of clouds, because the brightness value of land and sea is lower than cloud, and the brightness value of land and sea is continually varied by altitude of sun, the cloud area cannot be estimated by threshold processing. In this study, Variation character of brightness value is classified in each area, and the processing method of each area is proposed based on this variation character. In land area, there is correlation between brightness value of VIS and IR image if the area is not covered by cloud. Thus, the object domain is estimated cloud area using the correlation between them. In sea area, due to temperature is stable, cloud area is estimated by background subtraction method. This method was used to estimate and evaluated in the 202 GMS-5 images. The evaluated results shown that the proposed method is more accurate than the previous method, which estimated by threshold processing (Omi, 2003).

AB - This paper proposes a method that estimates the position of clouds from VIS images (visible), and IR images (infrared) of GMS (Geostationary Meteorological Satellite). In estimating the position of clouds, because the brightness value of land and sea is lower than cloud, and the brightness value of land and sea is continually varied by altitude of sun, the cloud area cannot be estimated by threshold processing. In this study, Variation character of brightness value is classified in each area, and the processing method of each area is proposed based on this variation character. In land area, there is correlation between brightness value of VIS and IR image if the area is not covered by cloud. Thus, the object domain is estimated cloud area using the correlation between them. In sea area, due to temperature is stable, cloud area is estimated by background subtraction method. This method was used to estimate and evaluated in the 202 GMS-5 images. The evaluated results shown that the proposed method is more accurate than the previous method, which estimated by threshold processing (Omi, 2003).

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KW - Cloud area

KW - GMS

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Robust cloud estimation for GMS images considering the dynamic changes on VIS/IR data

Abstract

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Keywords

ASJC Scopus subject areas

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