Blind Image Deconvolution Motion Blur Estimation

This report discusses methods for estimating linear motion blur. The blurred image is modeled as a convolution between the original image and an unknown point-spread function. The angle of motion blur is estimated using three different approaches. The first employs the cepstrum, the second a Gaussian filter, and the third the Radon transform. To estimate the extent of the motion blur, two different cepstral methods are employed. The accuracy of these methods is evaluated using artificially blurred images with varying degrees of noise added. Finally, the best angle and length estimates are combined with existing deconvolution methods to see how well the image is deblurred.

[1]  Yitzhak Yitzhaky,et al.  Direct method for restoration of motion-blurred images , 1998 .

[2]  A.M. Tekalp,et al.  Survey of estimation techniques in image restoration , 1991, IEEE Control Systems.

[3]  R. Mersereau,et al.  Iterative methods for image deblurring , 1990 .

[4]  Pamela A. Delaney,et al.  Detection of linear features using a localized Radon transform , 1996, Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers.

[5]  Yitzhak Yitzhaky,et al.  Identification of the blur extent from motion-blurred images , 1995, Defense, Security, and Sensing.

[6]  M. Jamzad,et al.  Motion blur identification in noisy images using fuzzy sets , 2005, Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005..

[7]  King-Sun Fu,et al.  IEEE Transactions on Pattern Analysis and Machine Intelligence Publication Information , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Moon Gi Kang,et al.  An Algorithm To Extract Camera-shaking Degree And Noise Variance In The Peak-trace Domain. , 1998, International 1998 Conference on Consumer Electronics.

[9]  Yitzhak Yitzhaky,et al.  Restoration of an image degraded by vibrations using only a single frame , 2000 .

[10]  Stanley J. Reeves,et al.  Optimal space-varying regularization in iterative image restoration , 1994, IEEE Trans. Image Process..

[11]  Ioannis M. Rekleitis.  Steerable Filters and Cepstral Analysis for Optical Flow Calculation from a Single Blurred Image , 1996 .

[12]  A. Murat Tekalp,et al.  Blur identification using the bispectrum , 1991, IEEE Trans. Signal Process..

[13]  Anthony Vetro,et al.  IEEE TRANSACTIONS ON CONSUMER ELECTRONICS , 2008 .

[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]  Fionn Murtagh,et al.  Deconvolution in Astronomy: A Review , 2002 .

[16]  Konstantinos N. Plataniotis,et al.  Restoration of Motion Blurred Images , 2006, 2006 IEEE International Conference on Multimedia and Expo.

[17]  P. Toft.  The Radon Transform - Theory and Implementation , 1996 .

[18]  K. V. Arya,et al.  Identification of parameters and restoration of motion blurred images , 2006, SAC '06.

[19]  T. M. Cannon,et al.  Blind deconvolution through digital signal processing , 1975, Proceedings of the IEEE.

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

[21]  Ioannis M. Rekleitis,et al.  Visual Motion Estimation based on Motion Blur Interpretation , 1995 .