基于互补性的运动模糊图像复原方法
首发时间：2017-05-02
摘要：图像复原的目的是将原始图像从观测到的降析图像中恢复出来,在多帧图像复原算法中，输入图像帧的选择是很重要的问题，输入图像选择得好坏，直接影响最终的复原效果。本文针对多帧图像复原算法中的选帧问题，提出了一种基于互补性的运动模糊图像复原算法，首先根据图像纹理特性进行互补性计算，采用基于迭代的最大互补信息序列的选帧方法，挑选出最具互补性的多帧模糊图像，之后依据基于隐变量的稀疏建模的图像盲复原算法进行模糊核与潜在图像估计。实验表明，该方法的复原效果较好，优于单一的多帧图像复原方法。
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Multi deblurring method based on complementarity
Abstract：The purpose of image restoration is to recover the original image from the observed image. In the multi-frame image restoration algorithm, the selection of the input image frames is a very important problem. The input image's quality is good or bad, directly affect the final deblurring result. In this paper, a motion-blurred image restoration method based on the image's complementarity is proposed for the framing problem in multi-frame image restoration algorithm. First, the complementarity calculation is carried out according to the image texture characteristics. The most complementary multi-frame blurred image is selected by using the frame selection method based on the iterative maximum complementary information sequence. Then, using a coupled adaptive sparse prior model to estimate the blur kernel and the potential image. Experiments show that the result by using the proposed method is better than the traditional multi-image deblurring method.
Keywords： image restoration multi deblurring complementary
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