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统计分割方法
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     Methods of medical-image segmentation
     医学图像分割方法
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     statistical method;
     ⑤统计方法;
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     4. StatisticsValues are presented as x s .
     4.统计方法
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     Segmentation method of infrared image based on statistical model
     基于红外图像统计模型的分割方法
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     A synthetic statistic texture segmentation method
     一种综合的统计纹理分割方法
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  statistical techniques
The heart rhythm variability, using standard statistical techniques of autocorrelation and spectral analysis, was analyzed.
      
The experimental results were treated by different statistical techniques: cluster analysis, multidimensional scaling, and multiple correspondence analysis.
      
These tasks can be solved based on an analysis of primary results of ITFD by selecting and using steady quantitative indexes of the total damaging using statistical techniques.
      
These tasks can be solved based on an analysis of primary results of ITFD by selecting and using steady quantitative indexes of the total damaging using statistical techniques.
      
The detection follows the linear regression method, which can be found in most textbooks about multivariate statistical techniques.
      
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This paper proposed a moving object segmentation method based on recursive high order statistics(HOS) used in videoconference sequence. The recursive high order statistics method can extract the signal from Gaussian noise. Because of using the former n image information, it can obtain such better estimates of HOS as the reduction of additive noise, detection of the small object and well performance of the segmentation compared with the classical higher order statistics method. The simulation test indicates...

This paper proposed a moving object segmentation method based on recursive high order statistics(HOS) used in videoconference sequence. The recursive high order statistics method can extract the signal from Gaussian noise. Because of using the former n image information, it can obtain such better estimates of HOS as the reduction of additive noise, detection of the small object and well performance of the segmentation compared with the classical higher order statistics method. The simulation test indicates the segmentation results are good.

提出了基于递归高阶统计的运动目标分割方案 ,主要用于会议电视图像序列 .与传统的高阶统计方法相比 ,基于递归高阶统计的分割方法从高斯噪声背景中提取信息 ,由于利用了前 n帧图像的信息冗余度 ,递归高阶统计方法可以更有效地减少噪声、检测小目标 ,并且提高了目标的分割准确度 .模拟试验结果显示 ,分割结果较好

 
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