First, the speckle noise is removed.
首先对原始图像除去斑点噪声；
The method not only removes the speckle noise, but also enhances contrast.
即去除了闪斑噪声，又提高了图像的清晰度。
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。
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。
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。
Finally, the broken lines due to speckle noise are connected by the high level grouping.
最后，通过高层编组方法连接由于噪声引起的直线缺损。
To solve this problem, a method to reduce speckle noise is proposed for digital holography.
针对这一问题，提出了一种基于微位移的数字全息散斑噪声抑制方法。
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。
Objective To remove the speckle noise in ultrasonic images by using anisotropic diffusion method.
目的将各向异性扩散方法应用于超声医学图像的去噪处理。
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。
By averaging the intensity fields, the speckle noise in the reconstructed images is well suppressed.
通过平均强度场，很好的抑制了强度再现像中的散斑噪声。
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。
An improved polarization recording approach to reduce speckle noise in digital holography is proposed.
提出了一种改进的数字全息散斑噪声抑制方法。
The testing image of shearography includes much speckle noise, so de-noising is a very important task.
散斑图像往往含有较大的噪声，如何对散斑图像进行降噪处理是一个非常重要的问题。
Speckle noise suppression gets stronger in homogeneous regions as the window size increases succeedingly.
在均匀区域，随着窗口大小的增大，斑点噪声抑制变得更强；
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 original centroid tracking algorithm is no longer suitable because of the speckle noise in ladar image.
然而常规形心跟踪算法因激光雷达图像受到散斑噪声影响而变得不适合。
The method can reduce the speckle noise effectively and improve the quality of the medical ultrasonic images.
该方法可以有效地去除超声图像斑纹噪声，提高图像的质量。
If unreasonable system parameters are selected, the detection performance will be severely limited by speckle noise.
如果系统参数选择不当，斑纹噪声将严重制约着系统的探测性能。
Due to low quality of ultrasound image by speckle noise, efficient denoising method is needed for processing and analyzing.
由于超声图像受散粒噪声影响往往像质较差，如何有效实现超声图像的去噪是后续处理和分析的关键。
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。
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。
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。
The arising mechanism, model and statistical characteristics of speckle noise are described and the popular filters are analyzed.
首先介绍了斑点噪声产生机理、模型和统计特征，对常用的图像滤波器进行了分析。
To recognize underwater target, extraction must be performed well because there is a lot of speckle noise in underwater laser images.
由于激光照射下的水下图像含有大量的散斑噪声，严重影响图像的质量。
In this paper, a new nonlinear weighted average multidirectional morphological filtering algorithm is proposed to suppress speckle noise.
提出了一种新的用于抑制散斑噪声的非线性加权均值多方向形态滤波算法。
This paper presents an approach for the speckle noise reduction in three-dimensional surface laser light sensing: surface light scanning.
提出一种激光片光三维传感中降低散斑影响的方法：片光面内移动扫描法。
A new nonlinear weighted average multidirectional morphological filtering algorithm is proposed, which is used in suppressing speckle noise.
提出了一种新的用于散斑噪声抑制的非线性加权均值多方向形态滤波算法。
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。
To recognize underwater target, segmentation must be performed efficiently because there is a lot of speckle noise in laser underwater images.
水下激光图像中夹杂着严重的散斑噪声，受其影响，要识别水下激光目标，就要对图像进行有效的消噪，然后进行目标分割。
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