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Spotlight SAR Images Restoration based on Tomography Model

机译:基于层析成像模型的Spotlight SAR图像恢复

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摘要

A novel approach for spotlight synthetic aperture radar (SAR) image restoration based on tomography model is presented for the characteristic of spotlight SAR image.Giving an initial guess value as the external incentives to detect SAR images of the internal features,the forward model is established to obtain the theoretical value for imaging.In order to overcome ill-posed problem of restoration and remain more texture information of targets in SAR image,adaptive regularization parameters are introduced,which make it possible to run synchronously with iteration operation and automatically modify the model parameters to the optimal value.Meanwhile,according to forward model,inversion model of SAR image is determined by using adaptive modified matrix. The updating value of image restoration is obtained by solving equations and setting the threshold as a condition for the termination of iteration so that the final results of the image restoration are obtained. The experimental results show that the proposed algorithm is effective for SAR image restoration with blurring and noises.
机译:提出了一种基于层析成像模型的聚光合成孔径雷达(SAR)图像特征恢复方法。以初始猜测值作为检测内部特征SAR图像的外部诱因,建立了前向模型。为了克服成像的不适定问题,并在SAR图像中保留更多的目标纹理信息,引入了自适应正则化参数,可以与迭代操作同步运行并自动修改模型同时,根据前向模型,采用自适应修正矩阵确定SAR图像的反演模型。通过求解方程并将阈值设置为终止迭代的条件来获得图像恢复的更新值,从而获得图像恢复的最终结果。实验结果表明,该算法对于模糊和噪声的SAR图像复原是有效的。

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