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Proceedings Paper

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods
Author(s): Kuo-Hsien Hsu
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Paper Abstract

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel’s method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu’s, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu’s and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu’s method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Paper Details

Date Published: 8 November 2012
PDF: 13 pages
Proc. SPIE 8523, Remote Sensing of the Atmosphere, Clouds, and Precipitation IV, 85231X (8 November 2012); doi: 10.1117/12.2000465
Show Author Affiliations
Kuo-Hsien Hsu, National Space Organization (Taiwan)


Published in SPIE Proceedings Vol. 8523:
Remote Sensing of the Atmosphere, Clouds, and Precipitation IV
Tadahiro Hayasaka; Kenji Nakamura; Eastwood Im, Editor(s)

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