Multi-Shot Imaging
Multi-Shot Imaging
-- A Flexible Framework for High-Quality Computational Imaging
Haichao Zhang
Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2014
Abstract: Capturing high-quality images is usually one central goal in many imaging related scenarios. Considerable improvements have been made on the hardware side (e.g., the increasing resolutions of the camera sensor) to aid the users for achieving this goal. However, some factors such as camera shake during the photo capturing will still lead to degradations in the captured images, especially with the light-weight hand-held cameras such as those in smart phones. 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.
Results compared with state-of-the-art methods
1 Multi-Image Joint Alignment and Blind Deblurring
2 Image Super-Resolution with Blurry LR Images
3 Blind Super-Resolution: HR image from a Single LR image
Low-Res. (NN) Glasner et al. (ICCV'09) Michaeli & Irani (ICCV13) Proposed Method
[6] H. Zhang and D. Wipf. Non-uniform camera shake removal using a spatially-adaptive sparse penalty. In NIPS, 2013
[7] H. Zhang, D. Wipf, and Y. Zhang. Multi-image blind deblurring using a coupled adaptive sparse prior. In CVPR, 2013
Related Publication
Haichao Zhang and L. Cain, Multi-Shot Imaging: Joint Alignment, Deblurring and Resolution Enhancement, CVPR 2014 Paper
References
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