Abstract
Text images captured by the surveillance system or hand-hold cameras often suffer from motion blur due to the complex relative motion between the camera and the target during the exposure time. The accuracy of the kernel estimation and the effective priors for clear text images are two important keys in blind motion deblurring. A novel blind motion deblurring algorithm is proposed for text images in a complex scene. A criterion for selecting informative edges and an L 0 constraint are combined to improve the accuracy of the kernel estimation. Then, a fast non-blind deconvolution scheme is applied to accelerate the algorithm. Experimental results on text images show that the proposed method can achieve high-quality results with low computational complexity.
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