Single Image Motion Deblurring Using Transparency

One of the key problems of restoring a degraded image from motion blur is the estimation of the unknown shift-invariant linear blur filter. Several algorithms have been proposed using image intensity or gradient information. In this paper, we separate the image deblurring into filter estimation and image deconvolution processes, and propose a novel algorithm to estimate the motion blur filter from a perspective of alpha values. The relationship between the object boundary transparency and the image motion blur is investigated. We formulate the filter estimation as solving a maximum a posteriori (MAP) problem with the defined likelihood and prior on transparency. Our unified approach can be applied to handle both the camera motion blur and the object motion blur.

[1]  J. Todd.  Book Review: Digital image processing (second edition). By R. C. Gonzalez and P. Wintz, Addison-Wesley, 1987. 503 pp. Price: £29.95. (ISBN 0-201-11026-1) , 1988 .

[2]  Reginald L. Lagendijk,et al.  Identification and restoration of noisy blurred images using the expectation-maximization algorithm , 1990, IEEE Trans. Acoust. Speech Signal Process..

[3]  A. Murat Tekalp,et al.  Maximum likelihood image and blur identification: a unifying , 1990 .

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

[5]  William K. Pratt,et al.  Digital image processing, 2nd Edition , 1991, A Wiley-Interscience publication.

[6]  Deepa Kundur,et al.  A novel blind deconvolution scheme for image restoration using recursive filtering , 1998, IEEE Trans. Signal Process..

[7]  J. Paik,et al.  Out-of-focus blur estimation and restoration for digital auto-focusing system , 1998 .

[8]  David J. C. MacKay,et al.  Ensemble Learning for Blind Image Separation and Deconvolution , 2000 .

[9]  David Salesin,et al.  A Bayesian approach to digital matting , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[10]  Xinqiao Liu,et al.  Simultaneous image formation and motion blur restoration via multiple capture , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[11]  Khamami Herusantoso,et al.  Blind deconvolution using recursive inverse filtering , 2002 .

[12]  Ta-Hsin Li,et al.  A joint estimation approach for two-tone image deblurring by blind deconvolution , 2002, IEEE Trans. Image Process..

[13]  Jian Sun,et al.  Poisson matting , 2004, ACM Trans. Graph..

[14]  Shree K. Nayar,et al.  Motion-based motion deblurring , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Harry Shum,et al.  Bayesian Correction of Image Intensity with Spatial Consideration , 2004, ECCV.

[16]  Frédo Durand,et al.  Defocus video matting , 2005, ACM Trans. Graph..

[17]  Shmuel Peleg,et al.  Two motion-blurred images are better than one , 2005, Pattern Recognit. Lett..

[18]  Ramesh Raskar,et al.  Coded exposure photography: motion deblurring using fluttered shutter , 2006, SIGGRAPH 2006.

[19]  Amit K. Agrawal,et al.  Coded exposure photography: motion deblurring using fluttered shutter , 2006, ACM Trans. Graph..

[20]  Jianhong Shen,et al.  Deblurring images: Matrices, spectra, and filtering , 2007, Math. Comput..

[21]  Dani Lischinski,et al.  A Closed-Form Solution to Natural Image Matting , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Sundaresh Ram,et al.  Removing Camera Shake from a Single Photograph , 2009 .

[23]  Anil K. Jain.  Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.