基于自适应子空间重建的杂波抑制
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中国航天科工集团第三研究院,上海交通大学图像处理和模式识别研究所,上海交通大学图像处理和模式识别研究所,中国航天科工集团第三研究院,上海交通大学图像处理和模式识别研究所

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国家自然科学基金项目(面上项目,重点项目,重大项目)航空科学基金


Clutter suppression based on adaptive subspace reconstruction
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Institute of the Third Academy, China Aerospace Science and Industry Corporation,Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University,Institute of the Third Academy, China Aerospace Science and Industry Corporation,Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University

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    摘要:

    针对红外图像中背景杂波抑制困难的问题,提出了一种基于自适应子空间重建的杂波抑制方法.该方法首先根据稀疏编码理论,学习得到描述红外小目标的超完备字典,接着依次提取测试图像中的图像子块,并计算其在超完备字典中的表示系数,根据背景子块和红外小目标在稀疏域中表示系数的差异性,自适应地选择字典中的原子构成子空间对图像子块进行重构,从而得到原图与重构图像之间的残差图像.实验结果表明,该方法得到的残差图像,能够有效抑制杂波,提高红外图像的信噪比.

    Abstract:

    To suppress clutter in infrared image, a novel clutter suppression method based on adaptive subspace construction is proposed. An over-complete dictionary for modeling target is learned based on the sparse coding theory at first. Then the image patch is extracted from the test image in order . Representation coefficients are computed according to the dictionary. According to the difference in the representation coefficients of the target patch and the background patch in sparse domain, adaptive subspace is generated to reconstruct the image patch. Thus a residual image between original image patch and reconstructed patch is obtained. The experiment results show that the residual image obtained by the proposed method can effectively suppress background clutter and significantly improve signal-to-noise ratio of the infrared image.

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赵佳佳,唐峥远,杨杰,刘尔琦,周越.基于自适应子空间重建的杂波抑制[J].红外与毫米波学报,2012,31(1):47~51]. ZHAO Jia-Jia, TANG Zheng-Yuan, YANG Jie, LIU Er-Qi, ZHOU Yue. Clutter suppression based on adaptive subspace reconstruction[J]. J. Infrared Millim. Waves,2012,31(1):47~51.]

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  • 收稿日期:2010-12-31
  • 最后修改日期:2011-07-05
  • 录用日期:2011-07-10
  • 在线发布日期: 2012-02-28
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