A new fractional-order variational model for speckled de-noising

Meriem Hacini, F. Hachouf, K. Djemal
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引用次数: 3

Abstract

In this paper, a novel speckled image de-noising algorithm is proposed. A fractional-order multiplicative variational model is included as a multiplicative constraint in the regularization problem thereby the appropriate regularization parameter will be controlled by the optimization process itself. An adaptive selection method based on image regions property is used for the selection of the appropriate fractional-order value. The proposed algorithm not only overcomes the disadvantage of generating artificial edges but also has the advantage of de-noising and edges preservation.Experimental results show that the fractional order multiplicative variational model can improve the Peak Signal to Noise Ratio (PSNR) of image, preserve image structures and overcomes the disadvantage of generating artificial edges in the de-noising process.
一种新的分数阶变分散斑去噪模型
提出了一种新的斑点图像去噪算法。在正则化问题中引入分数阶乘法变分模型作为乘法约束,从而由优化过程本身控制合适的正则化参数。采用一种基于图像区域属性的自适应选择方法来选择合适的分数阶值。该算法不仅克服了人工生成边缘的缺点,而且具有去噪和边缘保持的优点。实验结果表明,分数阶乘变分模型可以提高图像的峰值信噪比,保留图像结构,克服了去噪过程中产生人工边缘的缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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