KEYWORDS: Image registration, Atmospheric turbulence, Turbulence, Image processing, Image restoration, Point spread functions, Signal to noise ratio, Motion models, 3D modeling, Information technology
This paper proposes a B-splines non-rigid registration method which applies to
atmospheric turbulence image, and then the method applies B-splines registration to multi-frames images
and puts forward a two-step control point adjustment method in the process of establishing. B-splines
controls point grid that makes image registration from “coarse” to “accuracy” in two steps. As a
consequence, experiments show that this method can simulate the details of turbulence degraded image.
Meanwhile, it achieves better registration results.
To improve the adaptive optics (AO) image’s quality, we study the AO image restoration algorithm
based on wavefront reconstruction technology and adaptive total variation (TV) method in this paper. Firstly, the
wavefront reconstruction using Zernike polynomial is used for initial estimated for the point spread function (PSF).
Then, we develop our proposed iterative solutions for AO images restoration, addressing the joint deconvolution
issue. The image restoration experiments are performed to verify the image restoration effect of our proposed
algorithm. The experimental results show that, compared with the RL-IBD algorithm and Wiener-IBD algorithm, we
can see that GMG measures (for real AO image) from our algorithm are increased by 36.92%, and 27.44%
respectively, and the computation time are decreased by 7.2%, and 3.4% respectively, and its estimation accuracy is
significantly improved.
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