Weighted linear motion deblurring with blur kernel estimation using consecutive frames

We propose an efficient algorithm for motion deblurring with kernel estimation using consecutive images. First we estimate motion vectors between consecutive images using optical flow and RANSAC. Then we calculate the weights of motion vectors. The proposed method is similar to Ben-Ezra's method. The main difference is that we use a single camera for estimating a blur kernel and capturing a blurred image. Experimental results have shown that the proposed method produces better deblurred images with less artifacts.