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相干斑噪声抑制
相关语句
  speckle noise removal
     The generative mechanism and conventional reduction methods of speckle noise, soft threshold and hard threshold methods in wavelet domain are investigated. 4) A SOT structure based method for SAR image compression is proposed, which integrated speckle noise removal and EZW algorithm.
     (4)提出一种新的SAR图像压缩方法,该方法结合了基于小波域空间树结构SOT的相干斑噪声抑制和EZW嵌入式零树编码算法,充分利用了SOT这个作为研究不同分辨率小波系数的空间相互关系的非常有效的数据结构。
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  “相干斑噪声抑制”译为未确定词的双语例句
     Research on Coherent Speckle Reduction in High Resolution SAR Image Based on Wavelet Transform
     基于小波变换的高分辨率SAR图像相干斑噪声抑制研究
短句来源
     A New Speckle Reduction Algorithm for High Resolution SAR Images
     一种新的高分辨率SAR图像相干斑噪声抑制算法
短句来源
     A method of SAR speckle suppression based on Kirsch direction template
     基于Kirsch方向模板的SAR相干斑噪声抑制方法
短句来源
     Experiments are made on SAR images by using the method, and the results are compared with those of the Lee filter.
     将该方法用于SAR图像相干斑噪声抑制 ,并与Lee滤波器的去斑效果进行了比较。
短句来源
     In this paper, in-depth studies of the SAR images speckle noise suppression and edge detection is carried out, with the sponsors of National Natural Science Foundation of China (No. 60472072), Specialized Research Foundation for the Doctoral Program of Higher Education (No. 20040699034), Aeronautical Science Foundation of China (No. 04I53070), and Special Subject of Governing Yellow River (2004SZ01-04).
     本文在国家自然基金(No.60472072)、博士点基金(No.20040699034)、航空基金(No.04153070)和黄委会治黄专项课题(2004SZ01-04)的资助下,对SAR图像的相干斑噪声抑制和边缘检测进行了深入研究,主要工作有:
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  相似匹配句对
     Study of SAR Speckle Noise Suppressing
     SAR相干噪声抑制
短句来源
     Speckle Noise Modeling and Reducing Technique of Synthetic Aperture Radar Images
     合成孔径雷达相干噪声建模与抑制技术
短句来源
     The Method and Study of Reducing Speckle Noise in SAR Image
     抑制SAR图像相干噪声方法研究
短句来源
     A Study of Speckle Reduction Algorithms of Synthetic Aperture Radar Images
     SAR图像相干噪声抑制算法的研究
短句来源
     Methods of reducing speckle noise in SAR image are discussed in this paper.
     探讨了抑制合成孔径雷达 (SAR)图像相干噪声的方法。
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  speckle noise removal
A new algorithm for speckle noise removal from interference patterns is proposed.
      
A new class of genetic-neuro-fuzzy filter is proposed to optimize the trade-off between speckle noise removal and edge preservation.
      
Efficient speckle noise removal algorithms may also find applications in real time surgical guidance assemblies.
      
Such a user interaction is in the first place useful for speckle noise removal from the ultrasound images.
      
Speckle noise removal is a research area by itself and is not a part of this work.
      


Methods of reducing speckle noise in SAR image are discussed in this paper.Traditional methods and recently wavelet transform for reducing speckle noise have some shortcoming,this study has satisfied result for reducing speckle noise by combining wavelet transform and Wiener filter.The better result of reducing speckle noise in case of preserving image edge and point target is presented by selecting the better wavelet basis after these effects are compared and observed.

探讨了抑制合成孔径雷达 (SAR)图像相干斑噪声的方法。传统噪声抑制和近年来小波变换去噪方法都有其不足之处。将小波变换和维纳滤波结合用于抑制SAR图像相干斑噪声 ,能够获得良好效果。通过比较观察在多个小波基情况下的噪声抑制结果 ,可以选择较好小波基 ,从而有较好的相干斑噪声抑制和保留图像边缘与点目标的滤波效果。

In this paper, we investigate the effect of speckle reduction on the classification of SAR images. The adaptive Kuan filter and wavelet soft-thresholding filter are respectively used in speckle reduction. The feature vector is composed of tone of image and four texture features based on the gray-level co-occurrence matrix (GLCM). The maximum likelihood classifier is used in image classification. The classification accuracy of the filtered images is compared with that of the unfiltered images. The results show...

In this paper, we investigate the effect of speckle reduction on the classification of SAR images. The adaptive Kuan filter and wavelet soft-thresholding filter are respectively used in speckle reduction. The feature vector is composed of tone of image and four texture features based on the gray-level co-occurrence matrix (GLCM). The maximum likelihood classifier is used in image classification. The classification accuracy of the filtered images is compared with that of the unfiltered images. The results show that although the quality of the image improves, the classification accuracy increases slightly after speckle reduction, and even decreases in some cases. This is due to the loss of some structural information in the course of filtering. Accordingly, we propose an improved feature extraction scheme, adopting the tone of filtered image combined with the texture features based on the GLCM of unfiltered image to form the feature vector. The experimental results show that the improved scheme can enhance the performance of classification.

研究了相干斑噪声抑制对合成孔径雷达 (SAR)图像分类的影响。分别采用Kuan自适应滤波和小波变换软门限滤波两种方法进行了相干斑噪声抑制 ;对于SAR图像的分类则采用了图像的灰度以及基于灰度级共生矩阵的 4种纹理特征 ,并利用最大似然分类器进行了监督分类。处理结果表明 ,相干斑噪声的抑制尽管可以提高SAR图像的质量 ,但是由于在相干斑噪声得到抑制的同时 ,地物的固有结构信息也受到损失 ,因此分类精度提高甚微 ,在某些情况下甚至有所下降。针对这种情况 ,提出了一种改进的特征提取方法 ,将基于原图像的灰度级共生矩阵提取的纹理特征与滤波后图像的灰度特征进行组合用于分类。实验结果表明 ,改进的特征提取方法提高了SAR图像的分类精度。

This paper presents a speckle reduction method for synthetic aperture radar(SAR) images based on stationary wavelet transform. SAR images be decomposed by stationary wavelet transform for several levels, the detail images toward 0 by threshold, the recovery SAR images is reconstructed. Experiment result shows that this method not only suppresses the speckle noise effectively, but also preserves as many target characteristics of original images as possible, the recovery SAR images's visual effect is satisfying...

This paper presents a speckle reduction method for synthetic aperture radar(SAR) images based on stationary wavelet transform. SAR images be decomposed by stationary wavelet transform for several levels, the detail images toward 0 by threshold, the recovery SAR images is reconstructed. Experiment result shows that this method not only suppresses the speckle noise effectively, but also preserves as many target characteristics of original images as possible, the recovery SAR images's visual effect is satisfying . The stationary wavelet thresholding de noising has obvious superiority compare to that of orthogonal wavelet.

提出了一种基于平稳小波变换的合成孔径雷达 (syntheticaperturradar,SAR)图像相干斑噪声抑制方法 ,即通过对SAR图像进行多层平稳小波变换 ,对平稳小波变换的细节图像信号进行阈值处理 ,以达到相干斑噪声抑制的目的 .实验结果表明 :此方法除了对相干斑噪声有很好的抑制作用外 ,还保留了尽可能多的目标特征和图像细节 ,有着较好的图像视觉效果 .

 
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