Motion blur adaptive identification from natural image model

This paper proposes a novel approach to estimate the parameters of motion blur (orientation and extension) simultaneously from the observed image. The motion blur estimation would be used in a standard non blind deconvolution algorithm, thus yielding a blind motion deblurring scheme. Our algorithm is based on the correlation between the modified logarithm power spectrum from natural image model and the blur kernel. The local minima of the modified spectrum are closer to the horizontal line, and thus more similar to the sinc function. Compared to previous estimation algorithm, the results are more accurate in noisy images.

[1]  José M. Bioucas-Dias,et al.  Blind Estimation of Motion Blur Parameters for Image Deconvolution , 2007, IbPRIA.

[2]  Norbert Wiener,et al.  Extrapolation, Interpolation, and Smoothing of Stationary Time Series , 1964 .

[3]  Brendt Wohlberg,et al.  Blind Image Deconvolution Motion Blur Estimation , 2006 .

[4]  Norbert Wiener,et al.  Extrapolation, Interpolation, and Smoothing of Stationary Time Series, with Engineering Applications , 1949 .

[5]  Leonidas J. Guibas,et al.  A metric for distributions with applications to image databases , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[6]  Yitzhak Yitzhaky,et al.  Identification of Blur Parameters from Motion Blurred Images , 1997, CVGIP Graph. Model. Image Process..

[7]  Edward H. Adelson,et al.  The Design and Use of Steerable Filters , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Hui Ji,et al.  Motion blur identification from image gradients , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Alfred S. Carasso,et al.  Direct Blind Deconvolution , 2001, SIAM J. Appl. Math..

[10]  William H. Richardson,et al.  Bayesian-Based Iterative Method of Image Restoration , 1972 .

[11]  Masatoshi Okutomi,et al.  Motion Blur Parameter Identification from a Linearly Blurred Image , 2007, 2007 Digest of Technical Papers International Conference on Consumer Electronics.

[12]  Anat Levin,et al.  Blind Motion Deblurring Using Image Statistics , 2006, NIPS.

[13]  N. Kopeika,et al.  Analytical method to calculate optical transfer functions for image motion and vibrations using moments , 1997 .

[14]  Til Aach,et al.  Blur identification using a spectral inertia tensor and spectral zeros , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[15]  L. Lucy.  An iterative technique for the rectification of observed distributions , 1974 .

[16]  Mansour Jamzad,et al.  Motion blur identification in noisy images using mathematical models and statistical measures , 2007, Pattern Recognit..

[17]  David Malah,et al.  Robust identification of motion and out-of-focus blur parameters from blurred and noisy images , 1991, CVGIP Graph. Model. Image Process..