Fast Algorithms for Estimating Aerosol Optical Depth and Correcting Thematic Mapper Imagery

Abstract

Remotely sensed images collected by the satellites are usually contaminated by the effects 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 reflectance from remotely sensed imagery by removing the atmospheric effects, 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 reflectance. In this paper we introduce an efficient algorithm to estimate the optical characteristics of the Thematic Mapper (TM) imagery and to remove the atmospheric effects from it. Our algorithm introduces a set of techniques to significantly improve the quality of the retrieved images. We pay a particular attention to the computational efficiency 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. (Also cross-referenced as UMIACS-TR-95-113)