Adaptive parametric estimator for complex valued images

Abhay Chaturvedi, Roshni Sharma, Damini Wadekar, A. Bhandwalkar, S. Shitole
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引用次数: 3

Abstract

Synthetic Aperture Radar (SAR) images are affected by speckle which has a multiplicative nature. It is a granular noise which appears due to coherent interference of radar waves reflected from elementary scatterers. The presence of speckle greatly affects the analytical ease in terms of image classification and segmentation. Despeckling filters such as Lee, Frost, Boxcar and other have been proposed to deal with the phenomenon of speckle. However, the major concern for such filtering approaches is the preservation of features like edges and point targets while filtering the homogeneous areas. In this paper, a new approach is proposed which deals with this issue by using a statistical method that filters the different image features separately. Thus, it provides a greater level of control on the filtering process. The performance of the proposed filter is analyzed using AIRSAR C-band dataset. The results show that the proposed filter gives a good performance in terms of despeckling the homogeneous region whilst preserving the edges and point targets.
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复值图像的自适应参数估计
合成孔径雷达(SAR)图像受到散斑的影响,散斑具有乘性。它是由于雷达波从基本散射体反射的相干干涉而产生的颗粒噪声。斑点的存在极大地影响了图像分类和分割的分析难度。诸如Lee、Frost、Boxcar等消斑滤光器已被提出用于处理散斑现象。然而,这种滤波方法的主要问题是在滤波均匀区域的同时保留边缘和点目标等特征。本文提出了一种利用统计方法分别过滤不同图像特征的新方法。因此,它提供了对过滤过程的更高级别的控制。利用AIRSAR c波段数据集分析了该滤波器的性能。结果表明,该滤波器在对均匀区域进行去斑处理的同时,保留了边缘和点目标。
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