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首页> 外文期刊>Applied Mathematical Modelling >Fraction-order total variation blind image restoration based on L1-norm
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Fraction-order total variation blind image restoration based on L1-norm

机译：基于L1范数的分数阶总变化盲图像复原

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摘要

A fraction-order total variation blind image restoration algorithm based on L1-norm was proposed for restoring the images blurred by unknown point spread function (PSF) during imaging. According to the form of total variation, this paper introduced an arithmetic operator of fraction-order total variation and generated a mathematical model of cost. Semi-quadratic regularization was used to solve the model iteratively so that the solution of this algorithm became easier. This paper also analyzed the convergence of this algorithm and then testified its feasibility in theory. The experimental results showed the proposed algorithm can increase the PSNR of the restored image by 1 dB in relation to the first order total variation blind restoration method and Bayesian blind restoration method. The details in real blurred image were also pretty well restored. The effectiveness of the proposed algorithm revealed that it was practical in the blind image restoration.
机译：提出了一种基于L1-范数的分数阶全变化盲图像恢复算法，用于恢复成像过程中未知点扩散函数（PSF）模糊的图像。根据总变异的形式，引入了分数阶总变异的算术运算符，并建立了成本数学模型。使用半二次正则化来迭代求解模型，从而使该算法的求解变得更加容易。本文还分析了该算法的收敛性，并从理论上证明了其可行性。实验结果表明，与一阶总变化盲恢复方法和贝叶斯盲恢复方法相比，该算法可以将恢复图像的PSNR提高1 dB。真实模糊图像中的细节也恢复得很好。所提算法的有效性表明该算法在盲图像复原中是可行的。

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