SAR image de-noising via grouping-based PCA and guided filter  

作　　者：FANG Jing HU Shaohai MA Xiaole 

机构地区：[1]Institute of Information Science,Beijing Jiaotong University,Beijing 100044,China [2]Shandong Province Key Laboratory of Medical Physics and Image Processing Technology,School of Physics and Electronics,Shandong Normal University,Jinan 250014,China

出　　处：《Journal of Systems Engineering and Electronics》2021年第1期81-91,共11页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(62002208;61572063;61603225);the Natural Science Foundation of Shandong Province(ZR2016FQ04)。

摘　　要：A novel synthetic aperture radar(SAR)image de-noising method based on the local pixel grouping(LPG)principal component analysis(PCA)and guided filter is proposed.This method contains two steps.In the first step,we process the noisy image by coarse filters,which can suppress the speckle effectively.The original SAR image is transformed into the additive noise model by logarithmic transform with deviation correction.Then,we use the pixel and its nearest neighbors as a vector to select training samples from the local window by LPG based on the block similar matching.The LPG method ensures that only the similar sample patches are used in the local statistical calculation of PCA transform estimation,so that the local features of the image can be well preserved after coefficients shrinkage in the PCA domain.In the second step,we do the guided filtering which can effectively eliminate small artifacts left over from the coarse filtering.Experimental results of simulated and real SAR images show that the proposed method outstrips the state-of-the-art image de-noising methods in the peak signalto-noise ratio(PSNR),the structural similarity(SSIM)index and the equivalent number of looks(ENLs),and is of perceived image quality.

关 键 词：synthetic aperture radar(SAR)image de-noising local pixel grouping(LPG) principal component analysis(PCA) guided filter 

分 类 号：TN957.52[电子电信—信号与信息处理] TN713[电子电信—信息与通信工程]