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 proceedingConference 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 languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume7107
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventRemote Sensing of Clouds and the Atmosphere XIII - Cardiff, Wales, United Kingdom
Duration: 2008 Sep 152008 Sep 17

Other

OtherRemote Sensing of Clouds and the Atmosphere XIII
CountryUnited Kingdom
CityCardiff, Wales
Period08/9/1508/9/17

Fingerprint

meteorological satellites
Weather satellites
Geostationary satellites
Satellite Images
Luminance
Brightness
brightness
Processing
Sun
Infrared radiation
Background Subtraction
thresholds
Infrared Image
estimates
subtraction
Estimate
sun
estimating
Temperature

Keywords

  • Area segmentation
  • Cloud area
  • GMS

ASJC Scopus subject areas

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

Cite this

Hiranaka, H., Van, A. N., & Aoki, Y. (2008). Robust cloud estimation for GMS images considering the dynamic changes on VIS/IR data. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 7107). [710702] https://doi.org/10.1117/12.800066

Robust cloud estimation for GMS images considering the dynamic changes on VIS/IR data. / Hiranaka, Hiroshi; Van, An Ngoc; Aoki, Yoshimitsu.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 7107 2008. 710702.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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