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Proceedings Paper

United estimation of blur distribution for space-variant rotation motion deblurring
Author(s): Ziyi Shen; Tingfa Xu; Ziwei Liu; Jie Guo; Hongqing Wang; Guokai Shi; Zhitao Rao
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Paper Abstract

The method for estimating the space-varying kernel for rotation motion which can’t be solved by a single kernel is proposed. After layering the image by multiplex difference of Gaussian model, the method estimate the rotary direction and the movement for each block in Fourier domain. An improved optimization for both direction and scale of different parts around the rotation center estimated with the same radius, through a constraint of United Least square Filter is taken in our algorithm to structure the blur path accurately. Aiming at the different position of the rotary region, combining the blur distribution estimated with an operator which created related to the spatial location, character and degree of rotation motion, here build a model to estimate a space-varying kernel for the rotation motion which is replaced by such pixels on the motion-blur-path with uniform and separate influence during the exposure in the original algorithm, it also could be used for space-variant de-blurring. Experimental results for synthetic and real images demonstrate the effectiveness of this algorithm.

Paper Details

Date Published: 21 September 2015
PDF: 10 pages
Proc. SPIE 9600, Image Reconstruction from Incomplete Data VIII, 960005 (21 September 2015); doi: 10.1117/12.2187333
Show Author Affiliations
Ziyi Shen, Beijing Institute of Technology (China)
Tingfa Xu, Beijing Institute of Technology (China)
Ziwei Liu, Beijing Institute of Technology (China)
Jie Guo, Beijing Institute of Technology (China)
Hongqing Wang, Beijing Institute of Technology (China)
Guokai Shi, Beijing Institute of Technology (China)
Zhitao Rao, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 9600:
Image Reconstruction from Incomplete Data VIII
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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