摘要
针对极化SAR图像目标检测问题,研究了极化SAR图像目标对比增强方法。特别针对待增强目标或待抑制杂波为极化特性复杂的非均匀区域的情况,提出了一种基于样本筛选的对比增强新方法。对于利用人工划分而粗略获得的目标及杂波样本候选区,该新方法首先基于极化分解理论筛选出具有不同散射机理类型的两类像素点,分别作为目标及杂波样本的初步筛选结果;然后在此基础上,基于Wishart统计检验理论进一步选取初步筛选结果中极化统计特性相近的像素点,以获得样本最终的筛选结果。通过上述筛选技术的综合利用,可有效改善直接采用人工划分样本进行目标对比增强的增强效果。基于E-SAR全极化实测数据的实验结果表明,该新方法是有效的。
Aiming to detect interesting targets in polarimetric SAR imagery, the problem of target contrast enhancement is studied in this paper, and a novel scheme based on the strategy of sample selection is proposed for heterogeneous areas having complex polarimetric properties. Firstly, a preliminary sample selection is achieved by treating two categories of pixels with different scattering mechanisms as sample pixels of target and clutter. Secondly, a further selection is complemented by a test statistic of wishart distribution, which treats pixels with similar polarimetric statistics as the final qualified samples. The novel scheme can enhance the performance merely acquired merely by the rough selection of pixel samples with manual intervention, and its validity is indicated by experimental results with E-SAR polarimetric SAR data sets.
出处
《中国图象图形学报》
CSCD
北大核心
2009年第11期2230-2236,共7页
Journal of Image and Graphics
基金
全国优秀博士学位论文专项资金项目(08100101)
教育部新世纪优秀人才计划项目(NCET-04-0997)
关键词
极化
SAR
目标对比增强
样本筛选
polarization, synthetic aperture radar（SAR） , target contrast enhancement, sample selection
