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A new cumulant-based active contour model with wavelet energy for segmentation of SAR images

机译:基于小波能量的基于累积量的主动轮廓模型用于SAR图像分割

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In this paper, a new algorithm for segmentation of Synthetic Aperture Radar images using the skewness wavelet energy has been presented. The skewness is the 3rd order cumulant which extracts the statistical properties of each region of a SAR image. SAR images have Nonlinearity in intensity inhomogeneities because of the speckle noise. The algorithm which we proposed in this paper is a region-based active contour model that is able to use the intensity information in local regions. This algorithm also is able to cope with the speckle noise and nonlinear intensity inhomogeneity of SAR images. We use the wavelet energy to analyze each sub-band of a SAR image. The results of the proposed algorithm on the test SAR images of agricultural and urban regions show a good performance of this method.
机译:本文提出了一种利用偏度小波能量分割合成孔径雷达图像的新算法。偏度是提取SAR图像每个区域的统计特性的三阶累积量。由于斑点噪声,SAR图像的强度不均匀性具有非线性。我们在本文中提出的算法是一种基于区域的活动轮廓模型,该模型能够在局部区域中使用强度信息。该算法还能够处理SAR图像的斑点噪声和非线性强度不均匀性。我们使用小波能量来分析SAR图像的每个子带。所提算法在农业和城市地区SAR图像测试中的结果表明该方法具有良好的性能。

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