Motion blur parameters identification from Radon transform image gradients

Motion blur is one of the most common blurs that degrades the images. Restoration of a motion blur image is highly dependent on the estimation of the parameters of the blurring kernel. The features of motion blur kernel are sharp dependent on the noise. This paper proposes a novel approach to estimate the parameters of motion blur (orientation and extension) from the observed image gradients. The image gradients enhance the periodic patterns of the motion blur kernel in the frequency space. And the proposed normalized Radon transform from the blurred image gradients could estimate the motion blur parameters in noisy image gradients. Compared to previous estimation algorithm, the results are more accurate when it comes to noisy images.