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

G. Akbarizadeh, G. Rezai-Rad
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引用次数: 5

Abstract

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.
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一种新的基于小波能量累积的SAR图像主动轮廓分割模型
提出了一种利用偏度小波能量对合成孔径雷达图像进行分割的新算法。偏度是提取SAR图像各区域统计特性的三阶累积量。由于散斑噪声的存在,SAR图像的强度不均匀性存在非线性。本文提出的算法是一种基于区域的活动轮廓模型,能够利用局部区域的强度信息。该算法还能处理SAR图像的散斑噪声和非线性强度不均匀性。我们利用小波能量对SAR图像的每个子带进行分析。在农业和城市区域的SAR测试图像上,该算法取得了良好的效果。
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