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

Junaid Ansari, S. Ghosh, Mukunda Dev Behera, Sharad Kumar Gupta
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引用次数: 2

Abstract

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.
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印度孙德尔本斯红树林Sentinel-1A SAR数据散斑去除技术研究
本研究对印度西孟加拉邦孙德尔本斯红树林的Sentinel-1A合成孔径雷达(SAR)图像进行了散斑噪声去除。比较了几种自适应和非自适应滤波器,如Median、Frost、Lee、Gamma最大后验(MAP)和Boxcar滤波器去除斑点噪声的能力。通过视觉解释和均方误差、平均差、峰值信噪比等定量指标对滤波过程得到的输出进行比较。结果表明,箱车滤波在视觉上保留图像中物体边缘的同时,能较好地去除散斑噪声。
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