Prediction of image propagation quality through the atmosphere:the dependence of atmospheric modulation transfer function on weather

Abstract

Using the atmospheric modulation contrast function area (MCFA) as a single-valued numerical criterion for image quality propagated through the atmosphere, a statistical study of atmospheric imaging data has led to the determination of regression coefficients with which to quantitatively predict, at visible and near-infrared wavelengths, effects of wind speed, air temperature, and relative humidity on image quality propagated through the atmosphere as functions of wavelength and of spatial frequency. Utilization of this procedure is quite simple: one merely plugs expected values for wind speed, air temperature, and relative humidity into the regression coefficient expression for the MCFA. The larger the expected MCFA, the better the expected image quality. Models are presented for desert and nondesert atmospheres. Preliminary experimentation indicates that the accuracy of the models is quite good and that the quality of image propagation through the atmosphere can be described as a simple function of basic macroscale meteorological dependences previously unknown. These fundamental meteorological parameters are part of weather forecasts measured worldwide, are simple and inexpensive to measure, and also can be used to determine the overall atmospheric modulation contrast function as a function of spatial frequency and meteorological conditions. An important advantage of this new approach is its simplicity as well as its accuracy.