Target extraction from clutter images using wavelet packet analysis

HyungJun Kim, P. Liang
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引用次数: 1

Abstract

We present a wavelet shrinkage method that yields high clutter suppression by using a best-tree wavelet packet analysis. An integrated automatic target recognition processor utilizing a wavelet packet transform and a shape extraction method is introduced to demonstrate the feasibility of using wavelet packet analysis for automatic target extraction from synthetic aperture radar (SAR) images. Two analysis procedures are processed independently and the two outputs from each process are combined to increase the detection performance. Experimental demonstrations of target extraction are also provided. The preliminary experiments show that target extraction using wavelet packet analysis has high detection performance as well as low false detection performance.
基于小波包分析的杂波图像目标提取
我们提出了一种利用最佳树小波包分析产生高杂波抑制的小波收缩方法。介绍了一种基于小波包变换和形状提取方法的综合自动目标识别处理器,验证了小波包分析用于合成孔径雷达(SAR)图像自动目标提取的可行性。两个分析程序独立处理,每个过程的两个输出相结合,以提高检测性能。给出了目标提取的实验演示。初步实验表明,基于小波包分析的目标提取具有较高的检测性能和较低的误检性能。
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