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Removing Atmospheric Turbulence via Space-Invariant Deconvolution

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2 Author(s)
Xiang Zhu ; Dept. of Electr. Eng., Univ. of California, Santa Cruz, Santa Cruz, CA, USA ; Milanfar, P.

To correct geometric distortion and reduce space and time-varying blur, a new approach is proposed in this paper capable of restoring a single high-quality image from a given image sequence distorted by atmospheric turbulence. This approach reduces the space and time-varying deblurring problem to a shift invariant one. It first registers each frame to suppress geometric deformation through B-spline-based nonrigid registration. Next, a temporal regression process is carried out to produce an image from the registered frames, which can be viewed as being convolved with a space invariant near-diffraction-limited blur. Finally, a blind deconvolution algorithm is implemented to deblur the fused image, generating a final output. Experiments using real data illustrate that this approach can effectively alleviate blur and distortions, recover details of the scene, and significantly improve visual quality.

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:35 ,  Issue: 1 )