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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Quality Assessment of Despeckled SAR Images
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Quality Assessment of Despeckled SAR Images

机译：去斑SAR图像的质量评估

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摘要

In this paper, a novel method for the quality assessment of despeckled SAR images is proposed. This method is based on the observation that the perceived quality of despeckled SAR images is not always appropriately described by classical statistical and deterministic parameters that are proposed in the literature. Various evaluations are performed here. A preliminary visual qualitative evaluation is taken as a reference for the subsequent quantitative assessment. Then, a revised statistical analysis that can solve some of the drawbacks of previous methods is proposed; however, the statistical approach still has certain drawbacks. To address this problem, a new frequency analysis approach is first proposed, together with a definition of the appropriate indexes. In this way, it is possible to select the best filter in terms of noise reduction, edge and texture preservation, while limiting the effect of introduced distortions. While statistical analysis is widely used in the literature, frequency analysis has never been presented for this aim, especially for non-linear filters. We prove that frequency analysis can robustly identify the best filter, taking perceptual considerations into account, even when statistical analysis fails. Despeckling methods based on anisotropic diffusion algorithms are used for a comparison, but the proposed analysis can be applied to any filtering method. Experiments are presented with SAR images from the Italian Cosmo/Skymed constellation. Both Stripmap and Spotlight acquisitions have been evaluated, and to prove the validity of the proposed method with respect to different spatial resolutions and different classes of interest, various classes are considered.
机译：提出了一种去斑SAR图像质量评估的新方法。该方法基于以下观察：去斑点SAR图像的感知质量并不总是通过文献中提出的经典统计和确定性参数来适当描述。在此执行各种评估。初步的视觉定性评估将作为后续定量评估的参考。然后，提出了一种修正的统计分析方法，可以解决以前方法的一些缺点。但是，统计方法仍然存在某些缺陷。为了解决这个问题，首先提出了一种新的频率分析方法，并定义了适当的指标。这样，就可以在降低噪声，减少边缘和纹理保留方面选择最佳的滤波器，同时限制引入的失真的影响。尽管统计分析在文献中被广泛使用，但从未针对该目的提出频率分析，特别是对于非线性滤波器。我们证明，即使在统计分析失败的情况下，频率分析也可以在考虑到感知因素的情况下稳健地确定最佳滤波器。使用基于各向异性扩散算法的去斑点方法进行比较，但是所提出的分析可以应用于任何滤波方法。实验用来自意大利Cosmo / Skymed星座的SAR图像呈现。已经对Stripmap和Spotlight采集进行了评估，并且为了证明所提出方法相对于不同的空间分辨率和不同的关注类别的有效性，考虑了各种类别。

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