• DocumentCode
    8392
  • Title

    Removing Atmospheric Turbulence via Space-Invariant Deconvolution

  • Author

    Xiang Zhu ; Milanfar, Peyman

  • Author_Institution
    Dept. of Electr. Eng., Univ. of California, Santa Cruz, Santa Cruz, CA, USA
  • Volume
    35
  • Issue
    1
  • fYear
    2013
  • fDate
    Jan. 2013
  • Firstpage
    157
  • Lastpage
    170
  • 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.
  • Keywords
    deconvolution; geometry; image registration; image restoration; image sequences; regression analysis; splines (mathematics); B-spline-based nonrigid registration; atmospheric turbulence; fused image; geometric deformation; geometric distortion; image sequence; space invariant near-diffraction-limited blur; space-invariant deconvolution; temporal regression process; time-varying blur; time-varying deblurring problem; Deconvolution; Estimation; Image restoration; Imaging; Kernel; Noise; Vectors; Image restoration; atmospheric turbulence; nonrigid image registration; point spread function; sharpness metric; Algorithms; Artifacts; Artificial Intelligence; Atmosphere; Image Enhancement; Image Interpretation, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2012.82
  • Filename
    6178259