Analysis of statistical properties of atmospheric turbulence-induced image dancing based on Hilbert transform and dense optical flow

摘要

In this paper, the statistical properties of pixel displacements in turbulence degraded images are analyzed. Two main problems are addressed before that. One is the computation of pixel displacements. Dense optical flow is used since blur makes features like points and edges hard to track. The other one is selection of statistical samples. We use 2D-Hilbert transform to extract feature points, and only displacements at those points are considered. Statistical analysis includes distribution fitting, statistical parameters and normality test at different sample times and turbulence strengths. In the experiments, the method of computing distortions is first applied to simulated dataset to test its validity. Then this method of computing displacements and statistical analysis is applied to real-scene image sequences.