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Speckle noise suppression in SAR images (Oil spill images) using wavelet based methods and ICA technique

机译:使用基于小波的方法和ICA技术抑制SAR图像(溢油图像)中的斑点噪声

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Synthetic Aperture Radar (SAR) images are inherently degraded due to the coherent nature of the scattering phenomena called speckle. The presence of speckle decreases the utility of the SAR images by reducing the ability to detect ground objects. It affects the quality of the image adversely and hampers the observation of vital and crucial information present in the image. In this paper, we present speckle noise suppression techniques using wavelet decomposition and ICA methods. The algorithms viz., Projection Onto Approximation Coefficients (POAC), Projection Onto Span Algorithm (POSA) and Independent Component Analysis (ICA) are implemented on real SAR images and their results are tabulated. A comparison is made with standard speckle filters such as Lee filter, Frost filters, etc. The performance of our methods is measured in terms of Peak Signal-to-Noise Ratio (PSNR) values.
机译:由于称为斑点的散射现象的连贯性,合成孔径雷达(SAR)图像会固有地退化。斑点的存在通过降低检测地面物体的能力而降低了SAR图像的实用性。它不利地影响了图像的质量,并妨碍了对图像中存在的重要信息的观察。在本文中,我们提出了使用小波分解和ICA方法的斑点噪声抑制技术。在实际SAR图像上实现了算法,即投影到近似系数(POAC),投影到跨度算法(POSA)和独立分量分析(ICA)。与标准斑点滤波器(例如Lee滤波器,Frost滤波器等)进行了比较。我们的方法的性能是根据峰值信噪比(PSNR)值来衡量的。

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