Multi-shot imaging: Joint alignment, deblurring, and resolution-enhancement

Haichao Zhang, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Scopus citations

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.
Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherIEEE Computer Societyhelp@computer.org
Pages2925-2932
Number of pages8
ISBN (Print)9781479951178
DOIs
StatePublished - Jan 1 2014
Externally publishedYes

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