title: Removing atmospheric turbulence via space-invariant deconvolution.
abstract: 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.
authors.affiliation: Department of Electrical Engineering, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA. xzhu@ee.ucsc.edu
authors.forename: Xiang
authors.initials: X
authors.lastname: Zhu
authors.forename: Peyman
authors.initials: P
authors.lastname: Milanfar
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D001272:Atmosphere; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*