Blind motion deblurring from a single image is a challenging ill-posed problem. Significant progress has been made
since blur kernel estimation method using salient edge prediction on transfer region is proposed. However, as selection
rule for points to estimate the blur kernel has not been researched deeply, some texture and noise points were taken into
account for blur kernel estimating, which makes the existing methods not robust enough. This paper propose a robust
motion deblurring algorithm using salient edge prediction on transfer region, which employs a new metric to select
transfer region points for kernel estimation. A novel kernel refinement method with hysteresis thresholding is also
proposed and adopted by the algorithm to reduce the kernel noise. Extensive experiments show that the algorithm
achieves good results, while both the new metric and the novel kernel refinement method improve robustness of the
restoration algorithm.
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