Landsat TM Satellite Image Restoration Using Kalman Filters

Abstract

The quality of satellite images propagating through the atmosphere is affected by phenomena such as scattering and absorption of light, and turbulence, which degrade the image by blurring it and reducing its contrast. The atmospheric Wiener filter, which corrects for turbulence blur, aerosol blur, and path radiance simultaneously, is implemented in the digital restoration of Landsat Thematic Mapper (TM) imagery. Digital restoration results for Landsat TM imagery using the atmospheric Wiener filter were presented in the past. Here, a new approach for digital restoration of Landsat TM imagery is presented by implementing a Kalman filter as an atmospheric filter, which corrects for turbulence blur, aerosol blur, and path radiance simultaneously. Turbulence MTF is calculated from meteorological data. Aerosol MTF is consistent with optical depth. The product of the two yields atmospheric MTF, which is implemented in both the atmospheric Wiener and Kalman filters. Restoration improves both resolvable detail and contrast. Restorations are quite apparent even under clear weather conditions. Although aerosol MTF is dominant, slightly better results are obtained when the shape of atmospheric MTF includes turbulence, in addition to that of aerosol MTF, as shown by the use of criteria for restoration success. In general, the Kalman restoration is superior.