Motion de-blurring is a heated topic in the area of image quality enhancement

where kernel estimation is the key challenge. In this paper

we propose a new approach

which first performs segmentation on the input image and then deblur different regions. The method described in this paper includes the following steps: image decomposition

image segmentation

region-based kernel estimation and non-blind de-convolution

as well as image reconstruction by use of overlapping regions. Experimental results show that our method can outperform single kernel motion de-blurring methods in some cases.