United estimation of blur distribution for space-variant rotation motion deblurring

Ziyi Shen; Tingfa Xu; Ziwei Liu; Jie Guo; Hongqing Wang; Guokai Shi; Zhitao Rao

doi:10.1117/12.2187333

21 September 2015 United estimation of blur distribution for space-variant rotation motion deblurring

Ziyi Shen, Tingfa Xu, Ziwei Liu, Jie Guo, Hongqing Wang, Guokai Shi, Zhitao Rao

Proceedings Volume 9600, Image Reconstruction from Incomplete Data VIII; 960005 (2015) https://doi.org/10.1117/12.2187333
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

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.

Citation Download Citation

Ziyi Shen, Tingfa Xu, Ziwei Liu, Jie Guo, Hongqing Wang, Guokai Shi, and Zhitao Rao "United estimation of blur distribution for space-variant rotation motion deblurring", Proc. SPIE 9600, Image Reconstruction from Incomplete Data VIII, 960005 (21 September 2015); https://doi.org/10.1117/12.2187333

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