基于PDE和小波分解的SAR图像去噪研究

辽宁石油化工大学学报 ›› 2009, Vol. 29 ›› Issue (1): 65-68.

基于PDE和小波分解的SAR图像去噪研究

王桂楠,纪玉波^*

辽宁石油化工大学计算机与通信工程学院,辽宁抚顺113001

收稿日期:2008-09-19 出版日期:2009-03-25 发布日期:2017-07-05
作者简介:王桂楠(1982-),女,辽宁瓦房店市,在读硕士

Removing Speckles of SAR Image Based on Partial Differential Equation and Wavelet Decomposition

WANG Gui-nan, JI Yu-bo^*

School of Information and Communication Engineering, Liaoning University of Petroleum & Chemical Technology, Fushun Liaoning 113001, P. R. China

Received:2008-09-19 Published:2009-03-25 Online:2017-07-05

摘要/Abstract

摘要： 小波变换的优点在于其能够聚焦到图像的细微变化,并且有快速算法可以在短时间内完成其分解和
重构。偏微分方程的各向异性扩散能够很好地保留边缘和细节,但是由于SAR图像数据过大导致其迭代次数的增
加,使计算时间过长,算法效率降低。利用小波具有快速变换和“变焦距”的特性与偏微分方程的各向异性扩散模型
相结合的方法对SAR图像固有的相干斑进行去噪。实验结果证明,该方法不但具有很强的抑制噪声的能力、很好地
保持图像边缘和细节,而且提高了处理噪声的效率。

关键词: 偏微分方程 , 小波分解 , SAR图像 , 相干斑

Abstract: In the SAR image processing, wavelet transform has its unique advantages which analyzes image subtly and has fast algorithm that can resolve and reconstruct the image in short time. Partial differential equation's nonlinear diffusion could preserve the edges and textures, but the large SAR image statistics increase the iterative calculation and decrease the efficiency. The method of combining PDE(partial differential equation)'s nonlinear diffusion and wavelet transformation was proposed to remove speckles of SAR image. The experimental results show that the method can not only work quickly but also keep the image's edges and detail information well.

Key words: PDE , Decomposition , SAR image , Speckle

王桂楠,纪玉波. 基于PDE和小波分解的SAR图像去噪研究[J]. 辽宁石油化工大学学报, 2009, 29(1): 65-68.

WANG Gui-nan, JI Yu-bo. Removing Speckles of SAR Image Based on Partial Differential Equation and Wavelet Decomposition[J]. Journal of Liaoning Petrochemical University, 2009, 29(1): 65-68.