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