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Image Reconstruction of Static and Dynamic Scenes through Anisoplanatic Turbulence

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Document pages: 14 pages

Abstract: Ground based long-range passive imaging systems often suffer from degradedimage quality due to a turbulent atmosphere. While methods exist for removingsuch turbulent distortions, many are limited to static sequences which cannotbe extended to dynamic scenes. In addition, the physics of the turbulence isoften not integrated into the image reconstruction algorithms, making thephysics foundations of the methods weak. In this paper, we present a unifiedmethod for atmospheric turbulence mitigation in both static and dynamicsequences. We are able to achieve better results compared to existing methodsby utilizing (i) a novel space-time non-local averaging method to construct areliable reference frame, (ii) a geometric consistency and a sharpness metricto generate the lucky frame, (iii) a physics-constrained prior model of thepoint spread function for blind deconvolution. Experimental results based onsynthetic and real long-range turbulence sequences validate the performance ofthe proposed method.

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