Statistic estimation and validation of in-orbit modulation transfer function based on fractal characteristics of remote sensing images

• We build a model based on fractal principle of remote sensing images.
• The model parameters are analyzed.
• The model is used for modulation transfer function (MTF) estimation.
• The results of MTF estimation method we proposed are given.
• The MTF estimation method we proposed is verified by edge method.

This paper deals with the estimation of an in-orbit modulation transfer function (MTF) by a remote sensing image sequence, which is often difficult to measure because of a lack of suitable target images. A model is constructed which combines a fractal Brownian motion model that describes natural images stochastic fractal characteristics, with an inverse Fourier transform of an ideal remote sensing image amplitude spectrum. The model is used to decouple the blurring effect and an ideal natural image. Then, a model of MTF statistical estimation is built by standard deviation of the image sequence amplitude spectrum. Furthermore, model parameters are estimated by the ergodicity assumption of a remote sensing image sequence. Finally, the results of the statistical MTF estimation method are given and verified. The experimental results demonstrate that the method is practical and effective, and the relative deviation at the Nyquist frequency between the edge method and the method in this paper is less than 5.74%. The MTF estimation method is applicable for remote sensing image sequences and is not restricted by the characteristic target of images.