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An Efficient Implementation of Automatic Cloud Cover Assessment (ACCA) on a Reconfigurable Computer

Clouds have a critical role in many studies, e.g. weatherand climate-related studies. However, they represent a source of errors in many applications, and the presence of cloud contamination can hinder the use of satellite data. This requires a cloud detection process to mask out cloudy pixels from further processing. The trend for remote sensing satellite missions has always been towards smaller size, lower cost, more flexibility, and higher computational power. Reconfigurable Computers (RCs) combine the flexibility of traditional microprocessors with the power of Field Programmable Gate Arrays (FPGAs). Therefore, RCs are a promising candidate for on-board preprocessing. This paper presents the design and implementation of an RC-based real-time cloud detection system. We investigate the potential of using RCs for on-board preprocessing by prototyping the Landsat 7 ETM+ ACCA algorithm on one of the state-of-the art reconfigurable platforms, SRC-6E. Although a reasonable amount of investigations of the ACCA cloud detection algorithm using FPGAs has been reported in the literature, very few details/results were provided and/or limited contributions were accomplished. Our work has been proven to provide higher performance and higher detection accuracy.