Abstract
This paper proposes a novel technique for estimating focused video frames captured by an out-of-focus moving camera. It relies on the idea of Depth from Defocus (DFD), however overcomes the shortage of DFD by reforming the problem in a computer vision framework. It introduces a moving-camera scenario and explores the relationship between the camera motion and the resulting blur characteristics in captured images. This knowledge leads to a successful blur estimation and focused image estimation. The performance of this algorithm is demonstrated through error analysis and computer simulated experiments.
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