Abstract
This paper proposes using a mosaic image patches composed of the most informative edges found in the original blurry image for the purpose of estimating a motion blur kernel with minimum computational cost. To select these patches we develop a new image analysis tool to efficiently locate informative patches we call the informative-edge map. The combination of patch mosaic and informative patch selection enables a new motion blur kernel estimation algorithm to recover blur kernels far more quickly and accurately than existing state-of-the-art methods. We also show that patch mosaic can form a framework for reducing the computation time of other motion deblurring algorithms with minimal modification. Experimental results with various test images show that our algorithm to be 5-100 times faster than previously published blind motion deblurring algorithms while achieving equal or better estimation accuracy.
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Bae, H., Fowlkes, C.C., Chou, P.H. (2013). Patch Mosaic for Fast Motion Deblurring. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7726. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37431-9_25
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DOI: https://doi.org/10.1007/978-3-642-37431-9_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37430-2
Online ISBN: 978-3-642-37431-9
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