基于小波域正则化的毫米波图像重构
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摘要
毫米波被动成像具有全天时工作能力。与红外、可见光成像相比,其不足之处是分辨率较低,不能完全反映场景与目标的细节情况。采用小波域正则化方法,首先对毫米波图像进行小波域局部噪声方差估计,然后用自适应正则化方法重构超分辨率毫米波图像。毫米波图像处理的实验证明,该方法消噪效果明显,能锐化图像,保持图像细节。
Millimeter wave passive imaging has the ability to work day. But compared with infrared and visible light imaging, one of most important drawback in millimeter-wave passive imaging is the lower resolution,cannot fully reflect the scene and the target's detail. It is most important to improve millimeter-wave image resolution for better detecting and identifying the target. This paper, we use wavelet domain regularization method.Conduct millimeter-wave image wavelet domain local noise variance estimation, the latter with adaptive regularization method for reconstruction of high-resolution millimeter wave images. The experimental results show that this method significantly noise cancellation, sharpen the image, while preserving image detail.
Millimeter wave passive imaging has the ability to work day. But compared with infrared and visible light imaging, one of most important drawback in millimeter-wave passive imaging is the lower resolution,cannot fully reflect the scene and the target's detail. It is most important to improve millimeter-wave image resolution for better detecting and identifying the target. This paper, we use wavelet domain regularization method.Conduct millimeter-wave image wavelet domain local noise variance estimation, the latter with adaptive regularization method for reconstruction of high-resolution millimeter wave images. The experimental results show that this method significantly noise cancellation, sharpen the image, while preserving image detail.
引文
[1]李兴国,李跃华.毫米波近感技术基础[M].北京:北京理工大学出版社,2009.
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[5]矫媛,黄斌文.一种新的小波图像去噪方法[J].科技信息学报,2010,21(3):86-87.
[6]吕慧显,杨斌,李京.基于局部化自适应阈值的小波图像降噪[J].青岛理工大学学报,2010,31(2):118-122.
[7]刘成云,陈振学,马于涛.自适应阈值的小波图像去噪[J].光电工程,2007,34(6):77-81.
[8]钱苏敏,张琳絮,张云,等.基于小波阈值改进的去噪算法研究[J].光电工程,2012,31(5):49-51.
[9]周光祥,杨丹丹.基于自适应阈值的提升小波去噪方法[J].桂林电子科技大学学报,2012,32(2):150-154.
[10]刘毅文,李玲玲,李翠华,等.基于小波多阈值和子带增强的图像去噪[J].厦门大学学报,2012,51(3):342-347.
[11]王艳,胡章芳.图像复原中正则化参数的自适应选择方法[J].重庆邮电大学学报,2007,12,19(6):45-47.
[12]Chen W F,Chen M,Zhou J.Adaptively regularized constrained total least-squares image restoration[J].IEEE Transactions on Image Processing,2000,9(4):588-596.
[13]沈焕锋,李平湘.张良培.一种基于正则化技术的超分辨影像重建方法[J].中国图像图形学报,2005,10(4):436-440.
[14]苗晴,杨灵娥.基于空域正则化的模糊图像复原方法[J].佛山科学技术学院学报,2008,26(2):5-8.
[2]程正兴,杨守志,冯晓霞.小波分析的理论、算法、进展和应用[M].北京:国防工业出版社,2007.
[3]张彬,杨风暴.小波分析方法及其应用[M].北京:国防工业出版社,2011.
[4]王知强.一种基于新阈值函数的小波图像去噪算法[J].哈尔滨理工大学学报,2011,16(4):56-58.
[5]矫媛,黄斌文.一种新的小波图像去噪方法[J].科技信息学报,2010,21(3):86-87.
[6]吕慧显,杨斌,李京.基于局部化自适应阈值的小波图像降噪[J].青岛理工大学学报,2010,31(2):118-122.
[7]刘成云,陈振学,马于涛.自适应阈值的小波图像去噪[J].光电工程,2007,34(6):77-81.
[8]钱苏敏,张琳絮,张云,等.基于小波阈值改进的去噪算法研究[J].光电工程,2012,31(5):49-51.
[9]周光祥,杨丹丹.基于自适应阈值的提升小波去噪方法[J].桂林电子科技大学学报,2012,32(2):150-154.
[10]刘毅文,李玲玲,李翠华,等.基于小波多阈值和子带增强的图像去噪[J].厦门大学学报,2012,51(3):342-347.
[11]王艳,胡章芳.图像复原中正则化参数的自适应选择方法[J].重庆邮电大学学报,2007,12,19(6):45-47.
[12]Chen W F,Chen M,Zhou J.Adaptively regularized constrained total least-squares image restoration[J].IEEE Transactions on Image Processing,2000,9(4):588-596.
[13]沈焕锋,李平湘.张良培.一种基于正则化技术的超分辨影像重建方法[J].中国图像图形学报,2005,10(4):436-440.
[14]苗晴,杨灵娥.基于空域正则化的模糊图像复原方法[J].佛山科学技术学院学报,2008,26(2):5-8.