阈值收缩迭代算法在被动毫米波图像处理中的应用

Iterative Shrinkage-Thresholding Algorithms in Passive Millimeter Wave Image Processing Application

为了克服被动毫米波图像处理系统中数据量巨大,实时处理要求高的缺点,将阈值收缩迭代算法应于被动毫米波图像处理中,通过一个非自适应的基矩阵对原始图像信号进行变换,求解一个优化问题获得稀疏性最高的信号,可以在噪声干扰的情况下以极高的精度恢复出原始图像信号。将算法用于被动毫米波模拟图像的恢复实验,得到了很好的结果。因此,它是一种高效、可行的被动毫米波图像处理方法。

In order to overcome the disadvantage of the huge amount of data,real-time processing requirements in the passive millimeter wave image processing system,this paper applies iterative shrinkage-thresholding algorithms to millimeter-wave image processing.This method will transform the original image signal by a non-adaptive base matrix,and then solve an optimization problem for the highest sparsity of the signal.The method can recover the original image by sampling the signal in the case of noise interference signal by the high accuracy.Use this method for image restoration of passive millimeter-wave simulation,the result is perfect.Therefore,it is an efficient,feasible passive millimeter wave image processing method.