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Use of minimal inter-quantile distance estimation in image processing

机译：在图像处理中使用最小分位数距离估计

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摘要

Nowadays multichannel (multi and hyperspectral) remote sensing (RS) is widely used in different areas. One of the basic factors that can deteriorate original image quality and prevent retrieval of useful information from RS data is noise. Thus, image filtering is a typical stage of multichannel image pre-processing. Among known filters, the most efficient ones commonly require a priori information concerning noise type and its statistical characteristics. This explains a great need in automatic (blind) methods for determination of noise type and its characteristics. Several such methods already exist, but majority of them do not perform appropriately well if analyzed images contain a large percentage of texture regions, details and edges. Besides, many blind methods are multistage where some preliminary and appropriately accurate estimate of noise variance is required for next stages. To get around aforementioned shortcomings, below we propose a new method based on using inter-quantile distance and its minimization for obtaining appropriately accurate estimates of noise variance. It is shown that mathematically this task can be formulated as finding a mode of contaminated asymmetric distribution. And this task can be met for other applications. The efficiency of the proposed method is studied for a wide set of model distribution parameters. Numerical simulation results that confirm applicability of the proposed approach are presented. They also allow evaluating the designed method accuracy. Recommendations on method parameter selection are given.
机译：如今，多通道（多和高光谱）遥感（RS）广泛用于不同区域。可以恶化原始图像质量的基本因素之一，并防止从RS数据中检索有用信息是噪声。因此，图像滤波是多通道图像预处理的典型阶段。在已知的滤波器中，最有效的滤波器通常需要关于噪声类型及其统计特征的先验信息。这解释了用于确定噪声类型及其特征的自动（盲）方法中的大需求。已经存在了几种这样的方法，但如果分析的图像包含大百分比的纹理区域，细节和边缘，则大多数情况下不会适当地执行。此外，许多盲方法是多级，其中需要对下个阶段需要一些初步和适当的噪声方差估计。为了围绕上述缺点，下面我们提出了一种基于使用量级距离的新方法及其最小化，以获得适当准确的噪声方差估计。结果表明，数学上，可以将该任务制定为查找受污染的不对称分布模式。此任务可以满足其他应用程序。研究了所提出的方法的效率，用于各种模型分布参数。提出了鉴定了拟议方法的适用性的数值模拟结果。它们还允许评估设计的方法精度。给出了关于方法参数选择的建议。

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