One of the most common artifacts in digital photography is motion blur. When capturing an image under dim light by using a\nhandheld camera, the tendency of the photographer�s hand to shake causes the image to blur. In response to this problem, image\ndeblurring has become an active topic in computational photography and image processing in recent years. Fromthe view of signal\nprocessing, image deblurring can be reduced to a deconvolution problem if the kernel function of the motion blur is assumed\nto be shift invariant. However, the kernel function is not always shift invariant in real cases; for example, in-plane rotation of a\ncamera or a moving object can blur different parts of an image according to different kernel functions. An image that is degraded\nby multiple blur kernels is called a nonuniform blur image. In this paper, we propose a novel single image deblurring algorithm for\nnonuniform motion blur images that is blurred by moving object. First, a proposed uniform defocus map method is presented for\nmeasurement of the amounts and directions ofmotion blur. These blurred regions are then used to estimate point spread functions\nsimultaneously. Finally, a fast deconvolution algorithm is used to restore the nonuniform blur image.We expect that the proposed\nmethod can achieve satisfactory deblurring of a single nonuniform blur image.
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