卜方玲, 徐新. 一种基于小波分析的SAR图像斑点噪声滤波算法[J]. 武汉大学学报 ( 信息科学版), 2001, 26(4): 315-319,330.
引用本文: 卜方玲, 徐新. 一种基于小波分析的SAR图像斑点噪声滤波算法[J]. 武汉大学学报 ( 信息科学版), 2001, 26(4): 315-319,330.
BU Fangling, XU Xin. A Speckle Filtering Method of SAR Images Based on Wavelet Analysis[J]. Geomatics and Information Science of Wuhan University, 2001, 26(4): 315-319,330.
Citation: BU Fangling, XU Xin. A Speckle Filtering Method of SAR Images Based on Wavelet Analysis[J]. Geomatics and Information Science of Wuhan University, 2001, 26(4): 315-319,330.

一种基于小波分析的SAR图像斑点噪声滤波算法

A Speckle Filtering Method of SAR Images Based on Wavelet Analysis

  • 摘要: 利用多分辨率小波分析的理论,分析了SAR图像经多分辨率小波分解后生成的系列子图像中信号与斑点噪声能量分布特性及其信噪比的变化规律,提出了一种新的小波域斑点噪声的滤波算法,该滤波算法的阈值取决于各细节子图像的序列长度、方差及其所在的层次,并采用真实SAR数据和模拟加噪图像进行了试验。结果表明,该算法具有较强的噪声抑制和较好的边缘、细节保护能力及目视效果

     

    Abstract: The images of synthetic aperture radar(SAR) have been widely used in many important fields.Like any coherent imaging system,SAR systems are subject to speckle effects.This noise is conspicuous in single-look SAR images which disturb image interpretation and target classification.Therefore,to extent the use of SAR images,effective speckle reduction techniques are highly desirable. Based on the principle of multiresolution wavelet analysis,a new filter for suppression speckle in SAR is proposed.For images,an algorithm similar to the one-dimensional case is possible for two-dimensional wavelets and scaling functions obtained from one-dimensional ones by tensorial product.This kind of discrete two-dimensional wavelet transform leads to a decomposition of approximation coefficients at level j+1 in three components:the approximation at level j and the details in three orientations (horizontal,vertical,and diagonal).The "approximate image" at level j is composed of the low frequency parts in both row and column directions of approximate image at level j+1.And the there "detail images" contains its high frequency components separately in horizontal,vertical,diagonal directions.The approximate image is iteratively decomposed into four sub-images level by level.A pyramidal wavelet decomposing structure is thus constructed.It is tes-tified that the subspaces level of 4 or 5 is adequate for multiresolution wavelet analysis of an image (1024×1024).At each stage of the multiresolution pyramid,the approximate signal is low-pass filtered and decimated.And the wavelet coefficients are computed by high-pass filtering.It is proved that the signal energy concentrates on the wavelet coefficients of higher absolute value,and that the coefficients of high absolute value is more valuable than that of low absolute value in the signal wavelet reconstruction.It is also demonstrated that the effect of speckle is more serious in higher frequency parts,and the speckle decrease sharply as the image is low-filtered.So it can be considered that the speckle in 4 or 5 level approximate image can be ignored.The detail images of each subspace in which the ratio of signal to speckle is comparatively low are processed.The speckle of detail image at high frequency level is suppressed comparatively more by soft-threshold technique while the speckle at low frequency is suppressed comparatively less.The filter's threshold is computed according to the number of level,the variance and the length of each detail images. The result image which is reconstructed by the processed detail images of each level is estimated through the effect of vision,the quantitative analysis such as mean,standard and variance,and the analysis of preservation of edge and detail.The filtering results of ERS-1 SAR image and image with simulated speckle show that the method proposed in this paper is satisfying in visual appearance,speckle suppression and detail preservation.

     

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