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。
The basic principle of speckle image correlation digital technique was introduced firstly in this paper.
文中首先介绍了散斑图像相关数字技术的基本原理，然后给出了变形计算公式。
This evaluation procedure can measure both the speckle suppression preformance and the loss of original information of the image.
该评价体系能同时衡量各滤波算法对相干斑的抑制程度以及对图像原始信息的保持程度。
The main reason is that the resolution and contrast degree of the ultrasonic image itself is very low as well as the influence of intrinsic speckle noises.
其原因主要是超声图像本身分辨率、对比度较低，以及固有的斑点噪声的影响。
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。
And the displacement of speckle image reflects the distortion or displacement of objects.
而激光散斑图像的位移可以反映出物体的位移或形变。
With the technique improvement, focus is mainly put on four aspects: flow visualization, vision measuring technique, speckle measurement and image processing.
目前对该技术的改进主要集中在四个方面：流动可视化，视觉测量技术，斑点度量和图像处理。
An algorithm based on the anisotropic diffusion equation is presented to suppress the speckle noise of B-Scan ultrasound image.
提出了一种基于各向异性扩散方程的B超图像斑点噪声抑制的算法。
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。
Experimental results indicate this algorithm is a fast efficient algorithm to filter speckle noise in the underwater laser image.
实验表明这是一种有效的滤除水下激光图像散斑噪声的快速滤波算法。
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。
The basic principle of speckle image correlation digital technique was introduced firstly in this paper. And Calculation formula of deformation was also presented.
文中首先介绍了散斑图像相关数字技术的基本原理，然后给出了变形计算公式。
The relation between the correlation function of intensity variation and surface roughness parameter is derived through analyzing the second-order statistical properties of the speckle image.
分析此散斑图像的二阶统计特性，导出了强度变化的相关函数和表面粗糙度参数之间的关系。
It also fits for dynamic displacement measurement when a high-speed image card was used. This technology expands digital speckle correlation method's application field.
使用高速图像采集卡，该方法可应用于斜光轴动态位移测量，拓展了数字散斑相关方法的应用范围。
A statistical noise model and a mathematical model for real speckle pattern are presented, and then, in view of the models, a new adaptive suboptimal image filtering approach is proposed.
本文介绍了一种实际散斑模式的数学模型和噪声统计模型，并提出了一种针对这种模型的自适应次优滤波方法。
The application of image processing technique in speckle interferometry is studied and a speckle image correlation digital technique is presented in the paper.
研究图像处理技术在散斑测量中的应用，提出了一种散斑图像相关数字技术。
Results the speckle noises in the original image were removed efficiently and the image edge details were reserved.
结果原图像中斑纹噪声被有效去除，图像边缘细节得以保留。
Speckle noises are similar to intramuscular fat pixels in beef image, and they must be removed if intramuscular fat pixels need to be correctly separated from beef muscle pixels.
牛肉图像中的斑点噪声与肌内脂肪的颜色特征相似，要准确提取牛肉图像中的肌内脂肪颜色特征，就必须先对斑点噪声进行滤除。
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。
However, for the actual optical system, its point image become a speckle because of diffraction of light and aberration.
对于实际光学系统，由于光的衍射和像差，使所成的点像为一弥散斑。
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。
An adaptive speckle filtering algorithm is proposed. It detects image points belonging to edge based on wavelet transform. Speckle are filtered according to detect results and multi-look.
提出了一种自适应斑点滤波算法，它基于小波变换检测图像中的边缘点，根据检测结果结合多视处理实现斑点滤波。
Based on the characteristics that the gray values of speckle image are weakening from both sides to the middle gradually, a new algorithm for speckle image processing is proposed.
针对散斑条纹的灰度值具有由两边向中间逐渐增强的特点，提出了一种新的计算机自动处理算法。
Finally, two experimental techniques -the reflective laser speckle photography and the image shift are presented to improve the measurement sensitivity.
本文最后提出了旨在提高测量灵敏度的二种实验技术-反射式激光散斑照相法与附加位移法。
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