Any image acquired by optical, eIectroopticaI or electronic means is likely to be degraded by the environment. The resolution of the acquired image depends on the total MTF (Modulation Transfer Function) of the system and the additive noise. Image restoration techniques can improve image resolution significantly; however, as the noise increases, improvements via image processing become more limited because image restoration increases the noise level in the image. The purpose of this research is to check and characterize the MTF and noise level influences on target acquisition probability by a human observer, i.e., checking the worthwhileness of the restoration. The immediate quantity that was measured is not the probability of detection, but rather the number of targets of different sizes and degradation recognized in each scene.Conditions when restoration is advisable are determined. Further research will include real-world target recognition probability.
The recently developed atmospheric Wiener filter, which corrects for turbulence and aerosol blur and path radiance simultaneously, is implemented in digital restoration of AVHRR imagery over the five wavelength bands of the satellite instrumentation. Restoration is most impressive for higher optical depth situations, with improvement with regard to both smallness of size of resolvable detail and contrast Turbulence modulation transfer function (MTF) is calculated from meteorological data. Aerosol MTF is calculated from optical depth, measured with a sun-photometer. The product of the two yields atmospheric MiT which is implemented in the atmospheric Wiener filter. Image restorations with accompanying atmospheric MTF curves are presented. However, restoration results using a simple inverse MTF filter were quite similar. This indicates the satellite images were characterized by very low noise and that turbulence jitter was very limited which, in turn, indicates that the twbulencc MTFs integrated upwards over the path length were small compared to aerosol MTFs.
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