摘要
由于合成孔径雷达(SAR)在农业、林业、水文、地矿、海洋、测绘等领域广泛应用,SAR图像质量和视觉效果提升成为了各国学者研究的热点问题。SAR图像的主要噪声源——相干斑噪声的抑制和去除显得越来越重要。本文通过分析了SAR图像的噪声成因以及其噪声模型。基于SAR图像的特性,本文结合小波变换和Contourlet变换各自的优点,提出了一种基于小波-轮廓波变换与图像循环平移结合的SAR图像去噪算法。本文所提出的算法不仅可以显著去除相干斑噪声,提高图像的信噪比,而且还具有平移不变性,可明显改善图像的视觉效果。实验结果表明:与单独使用小波变换去噪相比,本文算法的信噪比提高2分贝;与单独使用Contourlet变换去噪相比,本文的算法去噪后的图像更平滑,抑制了人造纹理产生,视觉效果得到了明显的改善。
As the synthetic aperture radar（SAR） has been widely used in agriculture,forestry,hydrology,mining,marine, mapping and other fields,the method to improve the image quality and visual effect of the SAR image has become a hot research problem for the international scholars.The suppression and removal of the speckle of SAR image has been more and more important.This paper analyzes how the noises of the SAR image are generated and their models are appropriate for the characteristics of SAR images. Then based on the advantages of wavelet transform and the Contourlet transform,we proposed a SAR image de-noising algorithm,which is Wavelet-Contourlet Transform with Cycle Spinning de-noising algorithm.The proposed algorithm can significantly suppress the speckle noise and improve the SNR of the image,also have the character of translational invariance,greatly improve the visual effect..Compared with just using Wavelet transform,the experiment result shows that the proposed algorithm＇s SNR increased 2dB.The proposed algorithm for SAR image de-noising makes the SAR images to be smoother than Contourlet transform and to be of much fewer man-made textures,the visual effects of the SAR image after de-nosing have been significant improvements.
出处
《信号处理》
CSCD
北大核心
2011年第6期837-842,共6页
Journal of Signal Processing
