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

机译:去斑点结构损失(DSL):一种用于衡量去斑点算法的结构保留能力的新指标

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摘要

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:本文提出了一种新的指标,称为去斑点结构损失(DSL),用于去斑点算法的性能评估,重点是结构信息的保存。通过考虑去斑点中最佳和最差结构保留的特性,DSL度量通过使用比率图像和无噪声参考图像在边缘点之间的局部相关性来检查比率图像中图像结构的存在,从而得出了目标和目标。去斑点算法的结构保持能力的定量度量。已经使用三种算法在模拟SAR图像的去斑点结果上测试了DSL度量,并且已经证明了DSL的效率。相比之下,其他五个常用的去斑点度量标准无法与去斑点结果以及比率图像中显示的结构损失保持一致。

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