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引用次数: 1

摘要

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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Target extraction from clutter images using wavelet packet analysis
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.
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Notice of RetractionMultichannel super high resolution. Novel channel equalization and multidimensional arbitrary pattern synthesis Improving the sidelobes of arrays fed by multiple-beam beam formers Antenna measures of merit for ultra-wide synthetic aperture radar Intelligent low rate compression of speckled SAR imagery Airborne ground moving target indication using non-side-looking antennas
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