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The method of how to find the blur parameters on an image was suggested when blurring factors of high frequency vibration and uniform linear motion happen simultaneously. Blurred images with various composite motion blur parameters were synthesized and analyzed using existing algorithms. It was found that cepstral analysis was capable of discerning the motion angles accurately when the directions of two motions are different. Along the motion angle, if the autocorrelation function of derivative image exists two close extreme points with positive and negative values separately and the space between two peak points is less than 4~ 5 pixels, the image would be blurred by high frequency motion, otherwise it would be blurred by uniform linear motion. Having determined the motion angle and motion style, the quadratic radon transform is the best way to obtain the blur amplitude for high frequency vibration. As for the uniform linear motion, the autocorrelation of image derivative is the best algorithm to obtain the blur length. [ABSTRACT FROM AUTHOR]

Abstract: Single image deblurring is a highly ill-posed problem and requires to be regularized. Many common forms of image prior have a major drawback that is unable to make full use of local image information. In this paper, we propose a single image deblurring method using novel image prior constraints. We establish a probabilistic model by enforcing inspired image prior constraints and adopt an advanced iterative scheme that alternates between blur kernel estimation and non-blind image restoration. To suppress ringing artifacts caused by inevitable blur kernel estimated errors, our method employs total variation image restoration and presents an alternation half-quadratic algorithm to solve the non-convex cost function. Finally, experiments show that our method has good performance in suppressing ringing artifacts, and makes a good balance between alleviating staircase effects and preserving image details. [Copyright &y& Elsevier]