From the research actuality of SAR-image processing and application, it is recognized that the pattern of SAR-image integrated with visible light-image, but this pattern is not perfect.
从目前SAR图像处理及其应用的研究现状来看，SAR图像和可见光图像相结合的处理和应用模式已得到公认，但是这种模式并不是完美的。
In the practical applications of SAR image classification, we have little prior knowledge about the classes and we rarely use polar information.
在实际的SAR图像分类应用中，我们关于类别的先验知识非常少，极化信息的利用也不充分。
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。
With the experiment result, the method is proved an efficient one of SAR image segmentation.
实验结果表明，该方法是一种有效的SAR图像分割方法。
Automatic ship detection is one of the important methods that make ship sailing safely. SAR image can be well applied to detect the ship.
船只检测是实现船只航行安全的重要方法之一，利用SAR图像可实现船只检测。
And also make SAR image processing and research become a hot topic in signal processing domain.
也使SAR图像的处理和研究成为当前信号处理领域的一个热点。
With the combination of SAR image features and fractal theory, a new method of edge detection by calculating the fractal dimension multiscalely is proposed.
将SAR图像的特点与分形理论相结合，提出了一种新的基于区域自选的多尺度分形维数边缘检测方法。
In order to improve the recognition effect and on the basis of analyzing the characteristic of MSTAR SAR image, a method of discrete wavelet analysis is proposed to extract features.
为了进一步提高MSTARSAR目标的识别效果，在分析了MSTAR SAR图像特点的基础上，提出了一种利用离散小波分解提取目标特征的方法。
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。
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。
The description and extraction of SAR image texture feature is important to texture segmentation.
SAR图像纹理特征的描述和提取是纹理分割的关键。
They also make SAR image processing and research become a hot topic in signal processing.
因此SAR图像的处理和研究成为当前信号处理领域的一个热点。
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。
Two step algorithm is proposed for unsupervised detection of linear structure from SAR image, in particular, the road network detection.
提出一种两步算法用于从合成孔径雷达(SAR)图像中无监督地提取线性特征，特别是公路网的提取。
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。
According to the Range Doppler equations, the geometric calibration of SAR image can be realized using SAR imaging parameters.
依据合成孔径雷达(SAR)距离方程和多普勒方程，用SAR成像参数可实现SAR图像的几何校正。
This paper presents an algorithm about SAR image change detection based on Principal Component Analysis (PCA).
该文提出一种基于主分量分析(pca)的SAR图像变化检测算法。
SAR image nonlinear iterative filtering approach based on correlated neighborhood model is presented, it can restrain error accumulation.
提出一种基于相关邻域模型可抑制误差积累的SAR图像非线性迭代滤波方法。
The experimental result proves that the proposed method is effective in edge detection of SAR image.
实验结果表明该方法是一种有效的SAR图像边缘检测方法。
Improving texture and preserving edge is the important target of synthetic aperture radar (SAR) image fusion.
提高纹理清晰度、保护边缘信息是合成孔径雷达(SAR)图像融合的重要目标。
The extracted line graph can be used for SAR image vectorization and comprehension etc.
提取的直线图可以用于遥感图像矢量化、自动目标识别等方面。
The size of filtering window has obvious impact on the effect of SAR image filtering.
滤波窗口大小的选择直接影响SAR图像滤波的效果。
Two segmentation methods of SAR image are proposed.
给出了两种SAR图像分割方法。
To solve the problem of losing part of edge in the SAR image de-noising, the edge of image can be preserves beforehand.
而常用的去噪算法在去噪的同时会损失图像的边缘信息，所以本文在去噪前预先保留了图像的边缘信息。
The geometric rectification of satellite SAR image becomes more and more important in order to avoid geometric distortion and locate the image accurately.
而对星载SAR图像进行几何校正处理，消除图像中的各种几何变形，从而实现精确定位也越来越重要。
In SAR image moving targets can be analysised, detected and detached by spectrum characteristics of the radar echoes, and the spectrum of moving tar-gets can be shifted to the origin.
图象中的动目标可以通过雷达回波的频谱特性进行分析、检测和分离，并能将动目标频谱移动到原点。
The test indicates that the method is better to been applied in extracting roads in full-polarimetric SAR image.
实验表明：该方法应用到全极化sar影像中的道路的提取中效果较好。
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。
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