The contents in the paper include acoustic image preprocessing, feature extraction of texture and shape, and classifier design.

内容涉及声图像的预处理、纹理和形状特征的提取，以及分类器的设计等。

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The description and extraction of SAR image texture feature is important to texture segmentation.

SAR图像纹理特征的描述和提取是纹理分割的关键。

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Accordingly, we propose an improved feature extraction scheme, adopting the tone of filtered image combined with the texture features based on the GLCM of unfiltered image to form the feature vector.

针对这种情况，提出了一种改进的特征提取方法，将基于原图像的灰度级共生矩阵提取的纹理特征与滤波后图像的灰度特征进行组合用于分类。

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