Due to the complicated background of objectives and the speckle noise in the high-resolution SAR images, it is almost impossible to extract roads directly from original remote sensing images.
由于高分辨率SAR图像中，目标背景复杂，同时由于受相干斑噪声的影响，因此很难直接从原始图像数据中提取道路特征。
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。
As the background of objectives in high-resolution SAR images is complicated and also affected by speckle noise, it is almost impossible to extract roads directly from original remote sensing images.
高分辨率SAR图象中目标背景复杂，同时由于受相干斑噪声的影响，很难直接从原始图象数据中提取道路特征。
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。
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。
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。
Speckle noise is an intrinsic property of Synthetic Aperture Radar (SAR) imagery.
相干斑噪声是SAR图像的固有特点。
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。
For the existence of strong speckle noise in SAR images, good segmentation results can't be gotten with traditional methods.
SAR图像存在强烈的相干斑噪声，传统方法不能很好对其分割。
Integrating the statistical characteristics of speckle noise in SAR images with wavelet-domain Markov random field (MRF) structure of images, a new wavelet-domain spec.
基于图像在小波域的马尔可夫随机场模型(MRF)结构，结合SAR图像中相干斑噪声的统计特性，本文提出了一种新的小波域相干斑抑制方法。
SAR is a coherent imaging system, so SAR images contain lots of Speckle noise.
SAR是一种相干成像系统，因此所成图像含有大量的相干斑噪声。
Because the serious noise of coherent speckle exists in the SAR imagery, some people believe that edge extraction using gradient for SAR imagery gives poor results.
但由于在合成孔径雷达图像中存在严重的相干斑噪声，有人认为使用灰度梯度提取合成孔径雷达图像的灰度边界得不到好的结果。
The practical RFI and speckle noise suppression techniques for ultra-wideband SAR are proposed.
提出了实用的超宽带sar射频干扰(RFI)和相干斑噪声抑制技术。
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 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。
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。
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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