In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quali...In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR interferograms.Apart from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this aspect.This paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram.Simultaneously,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed information.Experimental results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.展开更多
该文提出一种基于结构相似性指数(SSIM)的非局部均值(Non Local means,NL-means)滤波的合成孔径雷达(SAR)图像相干斑噪声抑制新方法。该方法用SSIM改进NL-means算法中小块相似性的度量,能利用结构信息来进行相干斑抑制。通过在真实SAR...该文提出一种基于结构相似性指数(SSIM)的非局部均值(Non Local means,NL-means)滤波的合成孔径雷达(SAR)图像相干斑噪声抑制新方法。该方法用SSIM改进NL-means算法中小块相似性的度量,能利用结构信息来进行相干斑抑制。通过在真实SAR图像上的实验表明,与GammaMAP滤波、CHMT算法、BLS-GSM算法、NL-means滤波相比,此方法在有效去除相干斑噪声的同时能更好地保持边缘结构信息。展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.62201051,62101039)in part by the Shandong Excellent Young Scientists Fund Program(Overseas)in part by the National Key Research and Development Program of China(No.SQ2022YFB3900055).
文摘In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR interferograms.Apart from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this aspect.This paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram.Simultaneously,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed information.Experimental results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.
文摘该文提出一种基于结构相似性指数(SSIM)的非局部均值(Non Local means,NL-means)滤波的合成孔径雷达(SAR)图像相干斑噪声抑制新方法。该方法用SSIM改进NL-means算法中小块相似性的度量,能利用结构信息来进行相干斑抑制。通过在真实SAR图像上的实验表明,与GammaMAP滤波、CHMT算法、BLS-GSM算法、NL-means滤波相比,此方法在有效去除相干斑噪声的同时能更好地保持边缘结构信息。
