Single-image motion deblurring using a low-dimensional hand shake blur model

Author

Baxansky, Artemy ; Tzur, Meir

Author_Institution

Zoran Corp., Haifa, Israel

fYear

2010

fDate

17-20 Nov. 2010

Abstract

A new algorithm for camera shake removal from a single image is presented. The motion blur point spread function (PSF) is represented in terms of the camera´s angular velocity, which is in turn approximated by a linear function of time. Edge spread functions are estimated from isolated edges within the image, and the information along different directions is combined in an optimization procedure to find the best matching PSF. The image is then restored using the Wiener filter, followed by a post-processing algorithm for ringing artifact reduction. Results on real images taken with a digital camera are demonstrated.

Keywords

Wiener filters; cameras; edge detection; image matching; image motion analysis; image restoration; optimisation; PSF; Wiener filter; angular velocity; camera shake removal; edge spread function; image matching; low-dimensional hand shake blur model; motion blur point spread function; optimization; post-processing algorithm; single-image motion deblurring; Angular velocity; Approximation methods; Digital cameras; Image edge detection; Image restoration; Pixel; blind deconvolution; camera shake; edge spread function; ringing artifacts;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Electronics Engineers in Israel (IEEEI), 2010 IEEE 26th Convention of

Conference_Location

Eliat

Print_ISBN

978-1-4244-8681-6

Type

conf

DOI

10.1109/EEEI.2010.5661911

Filename

5661911