该方法克服了均值漂移滤波存在块状效应的缺点。实验结果表明，该方法的整体性能优于均值漂移滤波、高斯滤波和中值滤波。
Experiments show that his method overcomes the defect of blocky effect in mean shift filtering, and is superior to mean shift filtering, Gaussian scale space filtering and median filter.
实验结果表明，与传统的中值滤波和均值滤波算法相比，该算法能够有效地去除高斯和脉冲噪声，同时能够保留更多的图像细节信息。
As a result, the experiment shows that the algorithm can effectively filter out Gaussian and impulse noises, as well as preserve more detailed information of the original image.
该算法可以直接应用于原系统的非线性模型当中，并且不需考虑系统噪声和量测噪声是否为高斯白噪声，都能得到很好的滤波效果。
It could be directly applied to the nonlinear model of the initial system, and could get good filtering result whether the system noise or measured noise was Gaussian or not.
结合中值滤波与小波去噪分别去除椒盐噪声和高斯噪声中的优势，提出了一种指纹图像混合去噪算法，并对其中的关键步骤进行了详细分析。
Combining the advantages of median filtering and wavelet transform in denoising salt and pepper and gauss noise, bring up a sort of mixing denoise algorithm, and analyze the critical steps on detail.
后者直接应用广义s变换的时频谱实现，用于含高斯白噪声信号的滤波，达到了突出有效信号和压制噪声的效果。
Another applied in filtering signal containing Gaussian white noise is computed directly by utilizing time-frequency spectrum of GST, which can enhance non-stationary signal and suppress noise.
以表面轮廓信号为例，结合图形和参数评估，研究了异常信号对高斯滤波性能的影响。
Taking the surface profile signal as an example, it analyzes the influence of outliers on the performance of Gaussian filtering with the help of the illustrations and evaluation parameters.
在中心极限定理和逼近理论的基础上，提出了一种用三角滤波器的级联来实现高斯滤波器的新方法。
On the basis of the central limit theorem and approximation theory, a new implementation of the Gaussian filter by cascaded triangle filters is presented.
文中对高斯信道和瑞利信道条件下的PN匹配滤波器的捕获性能进行了分析。
The acquisition performance of the PN matched filter is analysed under the condition of Gaussian channel and Rayleigh channel.
采用不同模板的均值滤波器和高斯滤波器来增强图像。
Textile images were enhanced by using mean filter and gaussian filter with different templates.
本文介绍了基于信号局部统计性质的、能同时压制加性高斯噪声和脉冲噪声的自适应顺序统计滤波器的基本原理。
The paper introduced the basic principles of adaptive L-order statistic filter based on local statistic properties of signals and the features of suppression of Gaussian noise and pulse disturbance.
文中用逼近法和双线性变换法，设计了用于圆度测量的高斯数字逼近滤波器，并给出了零相移的递归滤波算法，计算量小，计算效率高，易于实现。
A series of Gaussian digital approximation filters used in roundness measurement were designed on the basis of approximation method and bilinear transformation.
将TVAR模型的信号和反射系数矢量增广为状态矢量后，应用高斯粒子滤波器(GPF)估计TVAR的模型参数，构造了语音增强算法。
When TVAR model signal and reflection coefficients were extended to state vector, Gaussian Particle Filter (GPF) was applied to estimate parameters of TVAR model.
通过假设预测方位和实测方位差值服从零均值的高斯分布，利用贝叶斯理论来修正各滤波器的权重。
And the weight of each filter is updated using Bayes theory based on the assumption that the difference between estimate and measurement bearings obeys Gaussian distributions with zero mean error.
对中值滤波、均值滤波和高斯滤波的去噪效果进行了比较和分析，并将其应用到声呐图像的平滑过程中。
The results of noise reduction with a median filter, a average filter and a gauss filter are analyzed. The author applies these algorithms to the sonar image smoothing.
为了去除图像中混入的脉冲噪声和高斯噪声，提出了一种基于自适应中值滤波和自适应加权均值滤波的混合滤波方法。
To remove mixed impulse noise and Gaussian noise in digital images, a hybrid filter based on the adaptive median filter and the adaptive weighted mean filter are proposed.
根据三角窗函数的对称性和三角滤波器的递归性，给出了高斯滤波器的实用逼近算法。
According to the symmetry of the triangle window function and the recurrence relations of triangle filter, the practical algorithm of the approximated Gaussian filter is obtained.
该算法对红外图像处理过程中不同类型的噪声采用不同的方法滤波，有效地滤除了高斯噪声和脉冲噪声，同时增强了目标和背景中的边缘成分。
Different means are used for different kinds of noise respectively. The edges of target and background are enhanced and the elimination of Gauss noise and pulse noise are reduced.
为提高被动跟踪性能，提出了一种高斯和粒子滤波方法。
To improve the performance of passive tracking, the Gaussian sum particle filter (GSPF) was proposed.
采用维纳自适应滤波，抑制随机噪声和高斯噪声；
The proposed approach adopts adaptive filter to suppress random noise and Gauss's noise so as to enhance the SNR.
为改善多基地雷达系统对高机动目标的跟踪性能，提出了基于自适应高斯模型和扩展卡尔曼滤波(ekf)的机动目标跟踪算法。
Maneuvering target tracking algorithm based on adaptive Gauss model and EKF was built for improving the tracking performance in Multi-static systems.
对模糊的成像结果进行图像复原，采用高斯函数作为点扩展函数，应用于三维逆滤波和维纳滤波算法中，改进了这两种算法。
This paper used Gaussian function as point spread function, applying in inverse filtering algorithm and Wiener filtering algorithm and improving them.
研究了对局部平稳高斯色噪声混响模型和以局部平稳高斯色噪声混响模型为基础的分段匹配滤波和分段预白化匹配滤波检测算法。
Secondly, local stationary colored reverberation model and the block matched filtering and block prewhiten matched filtering detection methods which based on the model is studied.
研究了均值滤波、SUSAN滤波、高斯滤波和中值滤波技术，对缺陷图像进行了平滑去噪处理，最后选用快速中值滤波并取得了良好的效果，为下一步图像分割打好了基础。
The paper studies mean filter, SUSAN filter, median filter and gauss filter technology, and selects the fast median filter to get good smoothing result of pavement image.
本文提出了两种同时受脉冲噪声和高斯白噪声污染图像的基于区域生长的细节保护滤波器。
In this paper, two detail-preserving region-growing-based filters is proposed to deal with the noisy image.
利用中值滤波和基于小波变换的去噪声处理对同时含有高斯噪声和脉冲噪声的X线图像降噪方法进行探讨。
This paper evaluated median filter in company with wavelet transformation to process X-ray image that contained Gauss noise and impulse noise at the same time.
第二章引入非线性滤波理论，给出一类关于条件高斯过程的一维和多维非线性滤波估计。
In Chapter 2, we present nonlinear filtration theory, and find out the nonlinear conditional Gaussian filtering estimation under one dim and multi dims.
传统均值滤波和中值滤波对高斯型噪声和椒盐型噪声有着不同的滤波特性。
The conventional average filter and median filter have different filtering characteristics to Gauss noise and impulse noise.
主要工作如下：（1）通过几种常见滤波方法的实验与分析，改进了中值滤波法和高斯滤波法。
The main tasks are as follows:(1) According to experiment and analyzing of several common filtering methods, median filter method and Gaussian filter method were improved in this paper.
理论分析和实验结果表明，自适应指数滤波器的性能优于高斯滤波器。
The performance of this filter is compared with Gaussian filter theoretically and experimentally. It is shown that the performance of this filter is superior to Gaussian filter.
理论分析和实验结果表明，自适应指数滤波器的性能优于高斯滤波器。
The performance of this filter is compared with Gaussian filter theoretically and experimentally. It is shown that the performance of this filter is superior to Gaussian filter.
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