Fast Algorithms for Estimating Aerosol

Remotely sensed images collected by the satellites are usually contaminated by the eeects of the atmospheric particles through absorption and scattering of the radiation from the earth surface. The objective of atmospheric correction is to retrieve the surface reeectance from remotely sensed imagery by removing the atmospheric eeects, which is usually performed in two steps. First, the optical characteristics of the atmosphere are estimated and then the remotely sensed imagery is corrected by inversion procedures that derive the surface reeectance. In this paper we introduce an eecient algorithm to estimate the optical characteristics of the Thematic Mapper (TM) imagery and to remove the atmospheric eeects from it. Our algorithm introduces a set of techniques to signiicantly improve the quality of the retrieved images. We pay a particular attention to the computational eeciency of the algorithm, thereby allowing us to correct large TM images quite fast. We also provide a parallel implementation of our algorithm and show its portability and its scalability on several parallel machines.