Automatic Identification of Cloud Cover Regions Using Surf

Abstract

Weather forecasting has become an indispensable application to predict the state of the atmosphere for a future time based on cloud cover identification. But it generally needs the experience of a well-trained meteorologist. In this paper, a novel method is proposed for automatic cloud cover estimation, typical to Indian Territory Speeded Up Robust Feature Transform(SURF) is applied on the satellite images to obtain the affine corrected images. The extracted cloud regions from the affine corrected images based on Otsu threshold are superimposed on the artistic grids representing latitude and longitude over India. The segmented cloud and grid composition drive a look up table mechanism to identify the cloud cover regions. Owing to its simplicity, the proposed method processes the test images faster and provides accurate segmentation for cloud cover regions.

Assessment of Different Image Transformation Methods on Diwata-1 Smi Images Using Structural Similarity Measure

“…Several cloud mask generation techniques were researched to find the most applicable one for Diwata-1 data, including the Otsu process (Ramos et al, 2016) and the use of reflectance-based thresholds via adaptive average brightness (Roomi, Bhargavi & Banu, 2012). For the purpose of this paper, the threshold technique is used.…”