Satellite modulation transfer function estimation from natural scenes

We propose an in-orbit modulation transfer function (MTF) statistical estimation algorithm based on natural scene, called SeMTF. The algorithm can estimate the in-orbit MTF of a sensor from an image without specialized targets. First, the power spectrum of a satellite image is analyzed, then a two-dimensional (2-D) fractal Brownian motion model is adopted to represent the natural scene. The in-orbit MTF is modeled by a parametric exponential function. Subsequently, the statistical model of satellite imaging is established. Second, the model is solved by the improved profile-likelihood function method. In order to handle the nuisance parameter in the profile-likelihood function, we divided the estimation problem into two minimization problems for the parameters of the MTF model and nuisance parameters, respectively. By alternating the two iterative minimizations, the result will converge to the optimal MTF parameters. Then the SeMTF algorithm is proposed. Finally, the algorithm is tested using real satellite images. Experimental results indicate that the estimation of MTF is highly accurate.