摘要： 针对可见光航空遥感监测中，耀斑和云阴影等强噪音的干扰使水中目标很难直接发现，该文提出一种基于方向傅立叶能量谱和支持向量机的水面尾迹纹理自动提取算法，通过提取运动产生的尾迹实现对它们的准确识别。该算法将图像划分成大小相等的子图像，求取子图像的傅立叶能量谱，通过对传统的主成分分析进行改进求得子图像的纹理方向，根据纹理方向将能量谱划分为20个区域，将每个区域的能量谱和作为纹理特征。该纹理特征具有平移和旋转不变性等优点，并使用支持向量机作为分类器。实验结果表明该方法能够准确地提取运动目标产生的尾迹纹理。

关键词: 傅立叶能量谱, 主成分分析, 支持向量机

Abstract: To solve the problem that it is difficult to directly detect the object in the water for flares and cloud shadows, this paper proposes a water wake recognition method based on directional Fourier power spectrum and Support Vector Machines (SVM). This algorithm divides the whole image into sub-images with the same size, improves the traditional principal components analysis to obtain the sub-image direction from their Fourier power spectrum, partitions the power spectrum into 20 region, gets texture features from calculating the sum of every region, which are translation invariant and rotation invariant, and SVM is used as the classifier. Experimental results prove that the proposed algorithm can fetch the wake texture precisely.

Key words: Fourier power spectrum, principal components analysis, Support Vector Machines(SVM)

中图分类号: 

• TP18