The paper discusses automatic target detection in SAR images.
文中对SAR图像中的目标检测进行了研究。
These conclusions provide a guideline for feature extraction in SAR ATR.
这些结论可以有效的指导实际的SARATR中的目标特征提取。
Ship targets are generally present in SAR ocean imagery as bright points.
船在卫星SAR海洋图像中一般是以亮点的形式出现。
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。
In SAR imaging system two algorithms about azimuth prefilter are discussed in this paper.
针对SAR成像中的方位预滤波，讨论两种方位预滤波的算法。
Geometric distortion in SAR images is due to the measuring range characteristic of radar.
雷达的测距特性造成SAR图像出现几何失真。
You also examined different types of output and defined many of the flags used in SAR and iostat.
还研究了输出的不同类型，了解了在sar和iostat中使用的许多标志。
The method can provide flexible scan cycle which brings great freedom in SAR system designing.
该方法可以灵活安排扫频周期，从而使调频连续波SAR的系统设计具有更大的自由度。
The rank one phase estimation (ROPE) algorithm is a good estimator for phase error widely used in SAR.
秩-相位估计（ROPE）是一种性能较好的相位误差估计器，正被广泛地应用于SAR图像处理。
The statistical information of scattering centers in SAR DB images is proposed to add in segmentation.
本文研究了融入SAR图像散射中心的统计信息于目标分割。
The results demonstrate that it is a useful and promising method for oil spill detection in SAR images.
实验证明这是一种有效、有前途的SAR图像海洋表面油膜检测方法。
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。
Secondly, the characters existing in SAR oil spill and oil slick detection are summarized and introduced.
然后归纳总结了SAR图像海洋表面油膜及其检测的特点。
This work provides effective processing methods for ship imaging when the airborne radar works in SAR mode.
该文提供了机载雷达sar模式工作时对舰船成像的有效处理方法。
Although these methods can effectively reduce speckle in SAR images, they blur edge and texture information.
虽然每种去除斑点噪声方法都能有效去除斑点噪声，但都不同程度地损失了图像的边缘信息。
A new solution to internal wave detection and parameter estimation in SAR ocean image is presented in this paper.
提出了一种SAR图像海洋内波检测与参数估计的新方法。
Mapdrift algorithm is an autofocusing processing which can get correct Doppler frequency modulation slope in SAR processing.
在SAR成像中，MD算法是一种对多普勒调频斜率进行估计的自聚焦处理过程。
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。
The results of data processing show that the method is efficient, fast and accurate to detect the ship targets in SAR images.
对数据处理的结果表明，该方法能够有效、快速、准确地检测到SAR海洋图像中的舰船目标。
The problem of the detection and accurate positioning of ship wake linear feature in SAR ocean imagery is of great difficulty.
SAR海洋图像中航迹线性特征的检测和精确定位是一个困难的问题。
So the research of road detection and recognition in SAR images is not only significant in theory but also important in practice.
因此，SAR图像道路检测与识别的研究，不仅具有重要的理论价值，也具有重要的实际应用价值。
Speckle in SAR images will disturb classification accuracy. Vector filter of speckle is used to dual-frequency images before classification.
SAR图像的相干斑会影响图像的分类准确度和精度，在进行分类处理前，对双波段全极化SAR图像相干斑进行矢量滤波处理。
If the information about fixed clutter in SAR image can be used to suppress the background clutter, the detection of moving target will be easy.
利用单通道sar图像中静止背景的信息抑制静止杂波，可改善检测动目标的性能。
Intensive study of methods for the road detection and recognition and analysis of image features of roads in SAR images have been done in this thesis.
论文对SAR图像道路检测与识别方法进行了深入研究，分析了SAR图像中道路的影像特征，提出了一种SAR图像道路检测与识别的新方法。
Therefore, this paper develops an algorithm by using a variable threshold with constant false alarm rates to help suppressing the speckle in SAR images.
为此，本文提出了采用具有恒定误警率的阈值，以消除斑点噪声的影响。
Better experimental results are obtained and they show that the proposed method is effective and practical in detection and recognition of roads in SAR images.
可以看出，论文提出的方法能较好地检测与识别SAR图像中的道路，是比较有效可行的。
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 target recognition is an important process in SAR images interpretation and analysis. The process of recognition contains detection, discrimination, and recognition.
目标识别是SAR图像解译和分析的重要过程，识别过程主要包括检测、鉴别和识别三个阶段。
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。
It has huge signification to auto extract information of linear terrestrial object such as road, bridge, river and coastline from SAR image using computer in SAR image analysis.
在SAR图像分析中，如何利用计算机自动提取道路、桥梁、河流、海岸线等线性地物信息，具有重要的军用及民用意义。
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