Satellite image restoration filter comparison

Abstract

Many properties of the atmosphere affect the quality of images propagating through it by blurring it and reducing its contrast, as well as blur. Use of the standard Wiener filter for correction of atmospheric blur is often not effective because, although aerosol MTF (modulation transfer function) is rather deterministic, turbulence MTF is random. The atmospheric Wiener filter is one method for overcoming turbulence jitter. The recently developed atmospheric Wiener filter, which corrects for turbulence blur, aerosol blur, and path radiance simultaneously, is implemented here in digital restoration of Landsat TM (thematic mapper) imagery over seven wavelength bands of the satellite instrumentation. Turbulence MTF is calculated from meteorological data or estimated if no meteorological data were measured. Aerosol MTF is consistent with optical depth. The product of the two yields atmospheric MTF, which is implemented in the atmospheric Wiener filter. Restoration improves both smallness of size of resolvable detail and contrast. Restorations are quite apparent even under clear weather conditions. Techniques for high resolution restoration involving more versatile filtering techniques, such as Kalman's and adaptive methods, are considered by filter comparison.