• DocumentCode
    254196
  • Title

    Multi-shot Imaging: Joint Alignment, Deblurring, and Resolution-Enhancement

  • Author

    Haichao Zhang ; Carin, Lawrence

  • fYear
    2014
  • fDate
    23-28 June 2014
  • Firstpage
    2925
  • Lastpage
    2932
  • Abstract
    The capture of multiple images is a simple way to increase the chance of capturing a good photo with a light-weight hand-held camera, for which the camera-shake blur is typically a nuisance problem. The naive approach of selecting the single best captured photo as output does not take full advantage of all the observations. Conventional multi-image blind deblurring methods can take all observations as input but usually require the multiple images are well aligned. However, the multiple blurry images captured in the presence of camera shake are rarely free from mis-alignment. Registering multiple blurry images is a challenging task due to the presence of blur while deblurring of multiple blurry images requires accurate alignment, leading to an intrinsically coupled problem. In this paper, we propose a blind multi-image restoration method which can achieve joint alignment, non-uniform deblurring, together with resolution enhancement from multiple low-quality images. Experiments on several real-world images with comparison to some previous methods validate the effectiveness of the proposed method.
  • Keywords
    cameras; image capture; image enhancement; image fusion; image registration; image resolution; image restoration; blind multiimage restoration method; camera-shake blur; joint alignment; light-weight handheld camera; multiimage blind deblurring method; multiple blurry image registration; multiple image capture; multiple low-quality images; multishot imaging; nonuniform deblurring; resolution enhancement; single best captured photo; Cameras; Estimation; Image resolution; Image restoration; Joints; Kernel; Standards; joint alignment and deblurring; multi-shot imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
  • Conference_Location
    Columbus, OH
  • Type

    conf

  • DOI
    10.1109/CVPR.2014.374
  • Filename
    6909770