共查询到20条相似文献,搜索用时 180 毫秒
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针对电子倍增CCD(EMCCD)图像噪声密度随着增益的变化而变化,提出了一种基于噪声点检测的自适应模糊中值滤波算法。该算法由模糊滤波模块和自适应模块两部分组成。首先,该算法对滤波窗口内的中心点进行噪声检测;然后对检测为噪声的像素点引入双阈值,并根据引入的阈值和滤波窗口内的中值建立噪声点的模糊隶属函数,根据模糊隶属函数对噪声点进行滤波处理后输出;最后采用自适应模块调整待处理图像的像素。仿真及实验结果表明,新算法不仅能够有效地将图像中的噪声去除,而且很好地保护了图像中的细节和边缘,PSNR比传统的自适应中值滤波算法平均提高了15 dB以上;该算法在低噪声密度情况下性能明显好于其他中值滤波器,在高噪声密度情况下性能也比较稳定。 相似文献
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新型自适应Kalman滤波算法及其应用 总被引:5,自引:0,他引:5
为防止滤波发散和提高系统的实时性,提出了一种新的自适应Kalman滤波算法.该算法利用滤波异常判据获得一个滤波状态因子,通过滤波状态因子确定量测噪声协方差阵的值,在线调整噪声的统计特性实现自适应滤波.将该算法应用到惯导/双星组合导航系统中,并和常规Kalman滤波和简化的Sage-Husa自适应滤波算法进行仿真比较.仿真结果表明,在滤波精度与简化Sage-Husa自适应滤波相当的情况下,新算法简化了运算,提高了实时性. 相似文献
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为了有效滤除图像中大量存在的脉冲噪声,提出了一种基于Shearlet变换域改进自适应中值滤波方法。首先在对Shearlet变换进行深入分析的基础上,给出了Shearlet分解和重构基本步骤;然后实现对含噪图像进行多尺度Shearlet变换,对获得多个尺度下的分解系数采用从噪声检测、噪声滤波等环节改进的自适应中值滤波算法(IAMF)进行噪声抑制;最后实现滤波后分解系数重构。分别与经典中值滤波(MF)、自适应中值滤波(AMF)以及Shearlet变换域阈值法进行比较,实验结果表明,该滤波算法滤波性能较好。 相似文献
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《电光与控制》2017,(10)
当系统噪声和量测噪声统计特性不明确时,基于新息的自适应滤波对两种噪声进行估计时存在相关性,与实际情况不符而影响滤波精度。针对这种情况,提出改进的自适应滤波算法。首先建立了SINS/GPS紧组合导航系统空间方程;然后介绍了自适应卡尔曼滤波原理,指出了此算法对两种噪声估计出现相关性的原因,在此基础上提出了改进的自适应卡尔曼滤波算法,改进算法对系统噪声和量测噪声同时进行在线估计,解决了原算法存在的不足;通过半实物仿真实验可以看出,在系统噪声和量测噪声不明确时改进算法的估计精度,与原有算法在系统噪声和量测噪声已知时的估计精度相当,充分说明了改进算法的实用性。 相似文献
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变步长LMS算法及其在自适应消噪中的应用 总被引:8,自引:0,他引:8
介绍了一种新的变步长LMS自适应滤波算法。该算法具有较快的收敛速度和较小的失调,并且他不受已经存在的不相关噪声的干扰.将该算法应用于自适应噪声对消系统的仿真中,给出了计算机仿真结果,仿真结果与理论分析是一致的. 相似文献
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为了更好地恢复被高密度椒盐噪声污染的图像,在传统的自适应中值滤波算法的基础上提出了一种改进的自适应滤波算法。该算法将3×3矩形滤波窗口内极值点视为可疑噪声点,对可疑噪声点自适应调节滤波窗口大小进一步判断是否为噪声点;将噪声点区分为低密度噪声区噪声点和高密度噪声区噪声点,并分别用改进后的中值滤波算法、自适应修正后均值滤波算法处理,信号点保持不变。仿真结果表明,该算法处理速度快并且能够有效恢复被椒盐噪声(密度达80%)污染的图像,在去噪的同时能够很好地保护图像的细节。 相似文献
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基于最小均方自适应滤波器的无线光通信接收性能分析 总被引:2,自引:1,他引:2
无线光通信(OWC)系统采用大气通道作为传输媒介,而大气湍流效应引入了与信号强度有关的乘性噪声。为了消除乘性噪声所引起的信号衰落,分析并给出了基于最小均方(LMS)自适应滤波器的判决门限更新算法和稳态的抽头权系数相关矩阵算法。通过理论分析和计算机仿真,讨论了最小均方滤波器及其参数对无线光通信接收性能的影响。结果表明,采用非因果滤波器的无线光通信系统对湍流噪声具有明显的抑制作用。在弱湍流情况下,基于自适应最小均方滤波器的系统误码率(BER)低于10-8,可以满足网络通信的要求。通过分析不同滤波器阶数对误码率的影响表明,所采用的255阶的非因果结构的最小均方滤波器是最优的结构。 相似文献
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Lainiotis D.G. Papaparaskeva P. Kothapalli G. Plataniotis K. 《Geoscience and Remote Sensing, IEEE Transactions on》1996,34(4):886-891
The problem of estimating the return power in a LIDAR system in the presence of multiplicative noise (speckle) is addressed. A significant class of the partitioning approach is applied and comparisons are made with the extended Kalman filter (EKF) in the case where model parameter uncertainty exists. Through extensive simulations, the partitioned filter is shown to be significantly superior to the EKF algorithm 相似文献
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提出了一种自适应线性权值算法过滤传感网散粒噪声,算法首先提取散粒噪声的特征参数,然后对参数进行线性迭代变换,计算获得自适应权值参数,从而有效实现对散粒噪声的过滤。实验结果表明,该算法能过滤传感网中的散粒噪声,且效果良好。 相似文献
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Alin Achim Ercan E Kuruo?lu Josiane Zerubia 《IEEE transactions on image processing》2006,15(9):2686-2693
Synthetic aperture radar (SAR) images are inherently affected by a signal dependent noise known as speckle, which is due to the radar wave coherence. In this paper, we propose a novel adaptive despeckling filter and derive a maximum a posteriori (MAP) estimator for the radar cross section (RCS). We first employ a logarithmic transformation to change the multiplicative speckle into additive noise. We model the RCS using the recently introduced heavy-tailed Rayleigh density function, which was derived based on the assumption that the real and imaginary parts of the received complex signal are best described using the alpha-stable family of distribution. We estimate model parameters from noisy observations by means of second-kind statistics theory, which relies on the Mellin transform. Finally, we compare the proposed algorithm with several classical speckle filters applied on actual SAR images. Experimental results show that the homomorphic MAP filter based on the heavy-tailed Rayleigh prior for the RCS is among the best for speckle removal. 相似文献
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针对合成孔径雷达(SAR)图像特有的乘性噪声和非恒虚警统计特性很难正确提取目标边缘的问题,提出了在指数加权均值比(ROEWA)算子基础上寻找自适应的最佳局域Gabor滤波器进行目标边缘提取的方法。利用Gabor滤波器具有的多方向特性确定边缘方向,然后用最大似然估计纠正错误边缘方向,重新结合视觉细胞倍频程计算出Gabor函数的最佳局域滤波参数,提取出SAR图像的正确边缘。实验表明,该方法取得很好边缘提取效果,并且后期分割出的目标更符合实际目标形态,具有较强的通用性。 相似文献
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Describes a new fully motion-adaptive spatio-temporal filtering technique to reduce the speckle in ultrasound images. The advantages of this approach are demonstrated in echocardiographic boundary detection and in comparison with other techniques. The first stage of many automated echocardiographic image interpretation schemes is filtering to reduce the amount of speckle noise. The authors show how the two-dimensional least mean squares (TDLMS) filter can be configured as a motion-compensated filter for a time sequence of ultrasound images that eliminates the blurring associated with direct averaging. For an image corrupted by multiplicative speckle noise, the mode of the intensity distribution approximates the maximum likelihood estimator. In consequence, the temporal filter's output is biased towards the mode from the mean, using information contained within the speckle itself. A new adaptive algorithm for controlling the filter's convergence is also included. To evaluate performance, application to simulated, phantom, and an in vivo test sequence of the carotid artery are considered in comparison with other techniques. The effect of filtering on edges is of great importance, as these are used by subsequent image interpretation schemes. Quantitative measurements demonstrate the effectiveness of the Biased TDLMS filter, for both noise reduction and edge preservation. Echocardiographic images have a high noise content and suffer from poor contrast. Despite this challenging environment, the Biased TDLMS filter is shown to produce images that are better inputs for subsequent feature extraction. The benefits for echocardiographic images are highlighted by considering the problems of mitral valve analysis and extraction of the left atrium boundary. 相似文献
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Contourlet域超声图像自适应降斑算法研究 总被引:1,自引:0,他引:1
结合Contourlet系数的结构特点和超声图像相干斑乘性噪声模型,提出了一种新的基于Contourlet变换的斑纹噪声抑制算法.该算法通过计算方差一致性测度(VHM),用局部自适应窗口估计阈值萎缩因子,实现超声图像的降斑处理.实验结果表明,该算法在有效抑制斑纹噪声的同时,更有利于保持图像的边界信息,尤其适用于强噪声背景的超声图像. 相似文献
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Sen D. Swamy M.N.S. Ahmad M.O. 《Vision, Image and Signal Processing, IEE Proceedings -》2006,153(5):521-537
The problem of reducing the multiplicative noise corrupting a signal is discussed. A generalisation of the existing sampled function weighted order (SFWO) filter is proposed by relaxing the symmetry condition on the probability density function (PDF) of the noise. This generalised SFWO filter is then used within a homomorphic system to reduce the multiplicative noise. It is shown that the output from such a system is biased, and hence, a suitable bias compensation technique is suggested. An unbiased homomorphic system, whose design is based on the PDF of the corrupting multiplicative noise, is proposed to reduce the noise. Images generated by coherent imaging systems are always corrupted by speckle, a kind of multiplicative noise having a lognormal distribution. A filter called the mean median filter, to reduce additive white Gaussian noise, is first proposed and then used within the unbiased homomorphic system to reduce the speckle in images. The effectiveness of the various proposed algorithms is demonstrated and compared with that of some of the existing schemes through extensive simulations 相似文献