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A Study on Speckle Removal Techniques for Sentinel-1A SAR Data Over Sundarbans, Mangrove Forest, India

机译:Sundarbans,红山林,印度红山山区SAR数据散斑清除技术研究

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In this study speckle noise is removed from Sentinel-1A synthetic aperture radar (SAR) image of Sundarbans mangrove forest of West Bengal, India. Several adaptive and non-adaptive filters such as Median, Frost, Lee, Gamma maximum a posteriori (MAP) and Boxcar filter are compared for their capability in removing speckle noise. The output obtained from filtering processes are compared using visual interpretation and quantitative measures such as mean squared error, average difference, and peak signal to noise ratio, etc. The results show that boxcar filter performs better than other methods for removal of speckle noise while preserving edges of objects in the image visually.
机译:在这项研究中,斑点噪声从印度西孟加拉邦Sundarbans Mangrove森林的Sendinel-1A合成孔径雷达(SAR)图像中取出。比较了诸如中值,霜,李,伽马最大后的诸如中位数,霜,李,伽玛最大的自适应滤光器,以便它们在去除斑点噪声时的能力。使用视觉解释和定量测量比较从过滤过程获得的输出,例如平均平方误差,平均差和峰值信号到噪声比等。结果表明,BoxCar过滤器比其他方法更好地执行,以在保存时去除斑点噪音视觉上图像中对象的边缘。

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