Satellite Image Restoration Filter Comparison

摘要

The quality of satellite images propagating through the atmosphere is affected by phenomena such as scattering and absorption of the light, and turbulence, which degrade the image by blurring it and reducing its contrast. Here, a new approach for digital restoration of Landsat thematic mapper (TM) imagery is presented by implementing several filters as atmospheric filters which correct for turbulence blur, aerosol blur, and path radiance simultaneously. Aerosol modulation transfer function (MTF) is consistent with optical depth. Turbulence MTF is calculated from meteorological data. The product of the two yields atmospheric MTF, which is implemented in the atmospheric filters. Restoration improves both smallness of size of resolvable detail and contrast. Restorations are quite apparent even under clear weather conditions. Different restoration results are obtained by trying to restore the degraded image. Here, restorations results of the Kalman filter and the atmospheric Wiener filter are presented along with restoration results based on wavelets and multifractals. A way to determine which is the best restoration result and how good is the restored image is presented by a visual comparison and by examining several mathematical criteria.