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Resolving Objects at Higher Resolution from a Single Motion-Blurred Image Amit Agrawal and Ramesh Raskar CVPR
2007 (oral presentation)
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| Abstract: Motion blur can degrade the
quality of images and is considered a
nuisance for computer vision problems. In this paper, we show that
motion blur can in-fact be used for increasing the resolution of a
moving object. Our approach utilizes the information in a single
motion-blurred image without any image priors or training images. As
the blur size increases, the resolution of the moving object can be
enhanced by a larger factor, albeit with a corresponding increase in
reconstruction noise.
Traditionally, motion deblurring and super-resolution have been ill-posed problems. Using a coded-exposure camera that preserves high spatial frequencies in the blurred image, we present a linear algorithm for the combined problem of deblurring and resolution enhancement and analyze the invertibility of the resulting linear system. We also show a method to selectively enhance the resolution of a narrow region of high-frequency features, when the resolution of the entire moving object cannot be increased due to small motion blur. Results on real images showing up to four times resolution enhancement are presented. |
 Figure 1. Motion deblurring
using a traditional camera is a well-known but ill-posed problem. The flutter shutter camera, (proposed
by us in SIGGRAPH 2006) makes deblurring a well-posed problem. In this
paper, we show that motion deblurring can be used for resolution
enhancement. In practice, the resulting linear system remains ill-posed
using a traditional camera. By using a flutter shutter camera, the
conditioning of the system can be improved.
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