In this paper, SAR image speckle suppression is analyzed from the view of mathematical physics.
本文首先以数学物理的观点描述了SAR图像斑点噪声抑制问题。
Therefore, the suppression SAR image speckle noise, is an important issue of SAR imaging applications.
因此，抑制SAR图像的相干斑噪声，是SAR图像应用的重要课题。
The result shows that the algorithm filters the SAR image speckle noise efficiently, meanwhile it has much stronger ability to maintain the detail information.
结果表明，该算法在有效滤除SAR图像斑点噪声的同时，有更强的图像细节信息保持能力。
And then addressing SAR image speckle denoising, this dissertation proposed a new method based on bivariate shrinkage function combined with enhancement of wavelet significant coefficients.
其次针对SAR图像相干斑抑制问题，提出一种双变量收缩函数与小波系数显著性增强相结合的SAR图像的斑点抑制算法。
Speckle is one of the most important characters of SAR image.
相干斑点噪声是SAR影像的重要特征之一。
Methods of reducing speckle noise in SAR image are discussed in this paper.
探讨了抑制合成孔径雷达图像相干斑噪声的方法。
This algorithm can protect edge-characteristics of SAR image, along with a very good speckle reduction effort.
本算法能够完全保留SAR图像边缘特征，同时对相干斑具有较好的抑制能力。
Besides, many classification errors are caused by mixed pixels and speckle noise of the SAR image.
另外，许多分类错误是由SAR图像的像素点类别混淆和相干斑噪声干扰引起的。
But SAR image is liable to be affected by speckle noise, while almost spectral image have shortcomings of low contrast between object and background, edge blurring.
但SAR图像容易受到相干斑噪声的影响，而光谱图像普遍存在目标与背景对比度差、边缘模糊的缺点。
This paper focuses on the research of speckle filtering algorithms of SAR image and obtains some useful conclusions.
本文以机载合成孔径雷达图像相干斑滤波算法为研究内容，得出了一些有益的结论。
Speckle noise of Synthetic Aperture Radar (SAR) affects image quality and image interpretation seriously.
合成孔径雷达(SAR)的相干斑噪声严重影响图像质量，降低图像的可判读性。
The inherent speckle noise of SAR image affects the interpretation and the further processing, so it is important to suppress speckle noise of SAR images.
SAR图像固有的斑点噪声严重影响了图像的判读和后续处理，因此抑制SAR图像斑点噪声显得尤其重要。
The multiplicative nature of the speckle noise in SAR images is a big problem in SAR image segmentation.
乘法性质的SAR图像斑点噪声的SAR图像分割是一个大问题。
The method removes speckle noises of SAR image in effect, at the same time remaining the edge better.
该方法在有效去除SAR图像相干斑噪声的同时较好的保留了图像的边缘信息。
This paper discusses the problem of speckle reducing of SAR image based on nonlinear diffusion equation in order to reduce the noise of SAR image and improve the image's quality.
探讨SAR图像相干斑抑制的非线性扩散方程方法。以抑制SAR图像噪声，提高图像质量。
The speckle noises of SAR images make the image-interpretation complicated, and deteriorate the effectiveness of classification and information extraction procedures.
SAR图像斑点噪声使图像解译变得复杂，并降低了图像分类和信息提取的有效性。
In this paper, a new method of speckle reduction in polarimetric SAR image is proposed.
提出了一种新的极化SAR图像相干斑抑制的方法。
Besides, speckle simulation is discussed based on SAR image statistical characteristics in order to obtain more realistic SAR image.
另外，在SAR图像统计特征的基础上，进行SAR图像的乘性噪声模拟，可以满足更逼真的SAR场景需求。
The SAR image after speckle restraining was reconstructed using wavelet reconstruction technique. The experiment shows that speckle can be effectively restrained using this algorithm.
通过小波重构技术获得滤波后的SAR图象。实验证明，该方法能有效地抑制SAR图象中的斑点噪声。
For SAR image waters edge detection, the traditional algorithm can not suppress speckle noise, so there are many false edges in the results.
SAR图像水域边缘检测中，传统算法由于不能较好地克服斑点噪声影响，因此检测出的虚假边缘较多。
Because there is speckle noise in SAR image and the background clutter of water is usually very complex, weak target detection is a big challenge for conventional methods.
SAR图像存在相干噪声以及水面背景杂波的复杂性，传统方法对于弱目标检测存在困难。
Because of the backscatters, SAR images are contaminated by speckle noises which lower image quality and mask image structure. Therefore, noise-smoothing is the first step in the image processing.
SAR的后向散射成像机制决定了SAR图像中存在相干斑噪声，这些相干斑噪声降低了图像质量，掩盖了图像的细节结构，因此在SAR图像处理时通常先对图像进行去噪。
Because of the backscatters, SAR images are contaminated by speckle noises which lower image quality and mask image structure. Therefore, noise-smoothing is the first step in the image processing.
SAR的后向散射成像机制决定了SAR图像中存在相干斑噪声，这些相干斑噪声降低了图像质量，掩盖了图像的细节结构，因此在SAR图像处理时通常先对图像进行去噪。
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