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Scalar image processing filters for speckle reduction on synthetic aperture sonar images

机译:用于散斑减少合成孔径声纳图像的标量图像处理过滤器

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High resolution images provided by synthetic aperture sonar sensors (SAS) are of great interest, especially for the detection, location and classification of mines lying on the sea bed. But these data obtained by an active imagery system are highly corrupted by a noise called the speckle. To reduce this noise and suppress the spurious reflections it generates on the images, we propose to use different algorithms based on image processing techniques. Several image processing filters are tested and discussed. A comparative study of the results obtained on real SAS data is presented. The different filters are evaluated both visually and in terms of variance reduction.
机译:合成孔径声纳传感器(SAS)提供的高分辨率图像非常兴趣,特别是对于铺在海上床上的地雷的检测,位置和分类。但是,由主动图像系统获得的这些数据受到称为斑点的噪声的高度损坏。为了减少这种噪声并抑制它在图像上产生的虚假反射,我们建议使用基于图像处理技术的不同算法。测试并讨论了几种图像处理过滤器。提出了在实际SAS数据上获得的结果的比较研究。不同的过滤器在视觉上以及减少方差方面进行评估。

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