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As an ill-posed problem, multiframe blind super resolution imaging recovers a high resolution image from a group of low resolution images with some degradations when the information of blur kernel is limited. Note that the quality of the recovered image is influenced more by the accuracy of blur estimation than an advanced regularization. We study the traditional model of the multiframe super resolution and modify it for blind deblurring. Based on the analysis, we proposed two algorithms. The first one is based on the total variation blind deconvolution algorithm and formulated as a functional for optimization with the regularization of blur. Based on the alternating minimization and the gradient descent algorithm, the high resolution image and the unknown blur kernel are estimated iteratively. By using the median shift and add operator, the second algorithm is more robust to the outlier influence. The MSAA initialization simplifies the interpolation process to reconstruct the blurred high resolution image for blind deblurring and improves the accuracy of blind super resolution imaging. The experimental results demonstrate the superiority and accuracy of our novel algorithms. 相似文献
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水泥砼路面在使用过程中会产生诸多病害,本文尝试通过对旧水泥砼路面板唧泥、脱空等砼路面主要病害的分析,提出采用灌浆技术来解决此类病害.并对脱空的确定、灌浆加固机理、实施等进行了较详细的介绍和分析.从经济的角度评价了灌浆技术可行性. 相似文献