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Despeckling structural loss(DSL): A new metric for measuring structure-preserving capability of despeckling algorithms

机译:检测到结构损失(DSL):一种用于测量检测算法的结构保持能力的新度量

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In this paper, a new metric called despeckling structural loss(DSL) is proposed for performance assessment of despeckling algorithms with a focus on the preservation of structural information. By taking into account characteristics of the best and worst structure preservation in despeckling, the DSL metric examines the presence of image structures in ratio images by using local correlations between the ratio image and the noise-free reference image at edge points, leading an objective and quantitative measure of the structure-preserving capability of despeckling algorithms. The DSL metric has been tested on despeckling results of a simulated SAR image using three types of algorithms and efficiency of the DSL has been demonstrated. In comparison, the other five commonly used despeckling metrics fail to keep a consistency with the structural loss shown in despeckling results as well as ratio images.
机译:在本文中,提出了一种名为DescreChing结构损失(DSL)的新度量,以便对检测到算法进行性能评估,重点是结构信息的保存。 通过考虑到检测中最佳和最差结构保存的特征,DSL度量通过在边缘点处的比率图像和无噪声参考图像之间使用局部相关性,引导目标和 检测算法结构保存能力的定量措施。 已经在使用三种类型的算法和DSL的算法上测试了DSL度量的模拟SAR图像的检测结果。 相比之下,其他五个常用的飞晶度量指标未能与检测结果中所示的结构丢失保持一致性以及比率图像。

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