DE-NOISING OF SAR IMAGES BASED ON WAVELET-CONTOURLET DOMAIN AND PCA

被引:0
作者
Fang, Jing [1 ]
Wang, Dong
Xiao, Yang
Saikrishna, D. Ajay
机构
[1] Beijing Jiaotong Univ, Inst Informat Sci, Beijing 100044, Peoples R China
来源
2014 12TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP) | 2014年
关键词
SAR Image De-noising; Contourlet; Wavelet-Contourlet; Principal Component Analysis; SPECKLE REDUCTION;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
After analyzing the speckle model of SAR, a SAR image de-noising method based on Wavelet-Contourlet transform and principal component analysis is presented. Compared with Wavelet transform and Contourlet transform, Wavelet-Contourlet transform can express images more sparsely and obtain image structure better. Most of the existing methods for image de-noising rely on accurate estimation of noise variance, However, the estimation of noise variance is very difficult in Wavelet-Contourlet domain. Propose a new method for SAR image de-noising based on Wavelet-Contourlet transform and principal component analysis. Simulation results also corroborate that the proposed algorithm is efficient and performs significantly better in reducing the speckle noise, obtaining a higher peak signal-to-noise ratio, retaining the image details, and improving the visual effect.
引用
收藏
页码:942 / 945
页数:4
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