The construction of 2-D shift-invariance hybrid transform and its application in SAR image de-noising

被引：0

作者：

Qiu, Chaoyang ^{[1
]}

Liu, Shuaiqi ^{[2
]}

Wang, Qingbo ^{[1
]}

Hu, Shaohai ^{[2
]}

Xiao, Yang ^{[2
]}

机构：

[1] Radar and Avionics Institute of AVIC

[2] Institute of Information Science, Beijing Jiaotong University

来源：

Journal of Computational Information Systems | 2013年 / 9卷 / 24期

关键词：

DWT; HWT; Hybrid; SAR image de-noising; Shift-invariance; Transform;

D O I：

10.12733/jcis9035

中图分类号：

学科分类号：

摘要：

Some 2-D signals, such as SAR images, may have different probability distribution of noise and frequency interference in different directions. It poses the question of how to extract desired signals from such complicated environment of noise and interference. Then, a shift invariance hybrid transform using classical 2D DFT-DWT algorithm and Hilbert transform called 2D DFT-HWT is proposed in this paper. Its implementation is very simple and its directional selectivity has been enhanced. And to verify the effect of this transform, it is applied to remove the noise or interference in images from different directions. A new SAR image de-noising method based on the Wiener filter and wavelet domain Bayesian processor is proposed in this paper. It can effectively suppress speckle with better edge recovery. Numerical results show that the proposed de-noising method has better performance. Copyright © 2013 Binary Information Press.

引用

页码：10133 / 10140

页数：7

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