On-orbit spatial characterization based on satellite image structure

One practical way to characterize the spatial performance of an in-flight satellite optical imaging system is to determine the modulation transfer function (MTF) from its remotely sensed images on the ground. Currently, there are many MTF measurement techniques designed to provide accurate measurements for high-resolution imaging systems. However, these existing techniques usually rely on the presence and manual identification of a well-separated characteristics target. We introduce an insight to effectively estimate a degradation function based on the MTF by analyzing the nonlocal self-similarity characteristics, namely the structural component, in the observed image. To this end, this paper presents several strategies to realize the aim of this work. First, we propose a segmentation method to select the ideal candidates for MTF estimation. Second, we develop an adaptive structure selection method that removes detrimental structures and selects useful information for point spread function (PSF) estimation. Finally, we put forward a robust estimation method by introducing a spatial prior that is able to simultaneously suppress noises while preserving the sparsity and continuity of the PSF kernels. For the experiments, datasets used in the analyses are synthetically blurred images simulated from level 2A product of IKONOS and real remotely sensed images from level 0 product of RazakSAT. The experimental results demonstrate that the proposed method is practical and effective, with