一种高效去除椒盐噪声的中值滤波方法

提出了一种基于先检测、后滤波的椒盐噪声滤除算法．将像素值为0或255附近的像素点作为疑似噪声点,其余点为信号点．信号点不做任何处理,以保留更多的图像细节．而对于疑似噪声点,首先用改进的自适应极值中值方法进行噪声检测,并将检测结果记录在一个二值矩阵flag中,其中信号点记为1,噪声点记为0．然后根据图像像素值矩阵与flag的点积进行自适应中值滤波处理．实验结果表明,不仅对真实含噪图像处理有很强的适应性,而且对噪声密度高的图像,能在有效去除椒盐噪声的同时保护图像细节．在不同噪声率下均优于标准中值（SMF）滤波法及其一些改进方法,在噪声密度为10％～90％其峰值信噪比（PSNR）平均提高6dB．     

Adaptive Threshold Median Filter for Multiple-Impulse Noise

Attenuating the noises plays an essential role in the image processing. Almost all the traditional median filters concern the removal of impulse noise having a single layer, whose noise gray level value is constant. In this paper, a new adaptive median filter is proposed to handle those images corrupted not only by single layer noise. The adaptive threshold median filter （ATMF） has been developed by combining the adaptive median filter （AMF） and two dynamic thresholds. Because of the dynamic threshold being used, the ATMF is able to balance the removal of the multiple-impulse noise and the quality of image. Comparison of the proposed method with traditional median filters is provided. Some visual examples are given to demonstrate the performance of the proposed filter.     

基于噪声检测的自适应中值滤波算法

针对现有中值滤波算法对于高密度噪声图像以及纹理细腻图像的边缘处理能力欠佳的缺陷,提出一种基于噪声检测的自适应中值滤波算法.新算法根据噪声点与周围信息的关联程度将噪声点滤波值进行调整,从而更好的处理图像的细节部份.新算法中的自适应策略加强了滤波算法的去噪性能,使其对于含有任意噪声密度的图像也能很好的进行噪声滤除.通过仿真分析,新算法对于细节丰富的图像以及高密度噪声的图像滤波效果良好,有效的提高图像的峰值信噪比,其去噪效果相比其他方法更加优秀.     

基于神经网络噪声检测的自适应中值滤波器

针对椒盐噪声污染图像的滤波问题,提出了一种基于前馈神经网络的噪声检测器。基于这种噪声检测方法,采用自适应中值滤波算法,依据像素点的不同属性采用不同的滤波策略。实验结果表明,该算法在有效去除椒盐噪声的同时更好地保留了图像的边缘和细节,是一种有效的图像去噪方法。     

一种基于运动补偿的时域自适应视频降噪算法

视频信号内的噪声是信号中不希望出现的干扰部分,如果不加以有效的去除,会严重影响视频图像的质量.提出了一种基于运动补偿的自适应时域视频降噪算法.该方法通过运动补偿技术,在时域上跟踪并提取噪声.滤波的强度是根据物体运动轨迹上的运动强度自适应变化的.利用该算法,有效地去除了视频序列中的噪声,同时很好地保护了图像的细节.实验结果表明,采用本文的降噪算法处理后的视频图像质量明显优于采用空域的降噪方法的结果.     

消除噪声的一种变步长自适应滤波方法

在电子系统中不可避免地会受到噪声的干扰．用固定参数的滤波器进行消除噪声有其缺陷，它对信号与噪声的先验知识需要得较多．本文讨论了用一种变步长自适应滤波器消除噪声的方法．实验仿真证明这种方法能有效地去除弱信号中的噪声．     

消除噪声的一种变步长自适应滤波方法

在电子系统中不可避免地会受到噪声的干扰。用固定参数的滤波器进行消除噪声有其缺陷,它对信号与噪声的先验知识需要得较多。本文讨论了用一种变步长自适应滤波器消除噪声的方法。实验仿真证明这种方法能有效地去除弱信号中的噪声。     

A Fuzzy Switching Median Filter of Impulses in Digital Imagery (FSMF)

This paper proposed a fuzzy-based switching technique that aims at detection and filtering of impulse noises from digital images. Two types of noise models are used to obtain the noisy images. In this two-step process, the noise-free pixels are remained unchanged. The proposed detection algorithm uses 5 \(\times \) 5 window, based on all neighboring pixels on the center of the window of a noisy pixel. Two weighted median filters are devised, and a particular one is applied selectively to the noisy pixel based on the characteristics of the neighboring pixels within the window. Instead of a single threshold, two threshold values are used in the proposed fuzzy membership function to partition the noise level, and accordingly, a filtering method is applied to restore the corrupted pixel. Experimental results show that the proposed technique outperforms the existing impulse denoising methods in terms of peak signal-to-noise ratio and visual effects, with a comparable time complexity with the existing methods.     

一种改进的自适应中值滤波算法

针对传统自适应中值滤波算法的不足,文中提出了一种改进的自适应中值滤波方法,以有效的去除图像中的高密度脉冲噪声。第一,对于噪声点的检测,首先利用极大值和极小值的数量差找出可疑的噪声点,再利用邻域像素的相似性判断可疑点是否为噪声点。第二,对于滤波中值的计算,先把滤波窗口内具有相同灰度值的极值点压缩到一个,然后再计算中值。实验结果表明,该算法的滤波效果优于传统自适应中值滤波,且具有较好的稳定性。     

一种新的自适应多级中值滤波器

本文在多级中值滤波器（MLM）的框架下引入了自适应的机制，提出一种新的自适应多级中值滤器（简记AMLM），其中，自适应机制的建立借助于两个自适应子窗口，这两个子窗口根据各基本子窗口的顺序统计量（包括中值）的比较关系．以这些基本子窗口为基本单元自适应构成。新的滤波器与MLM有非常相近的细节保护特性，但是比MLM的滤噪能力有较大提高，此外，与MLM相同，AMLM不需要任何关于信号及噪声的先验知识。本文分析了新滤波器的特性，并给出了显示滤波器效果的实验结果。     

采用背景提取和自适应滤波的视频降噪算法

针对监控视频图像背景固定的特点,提出一种有效去除高斯噪声和脉冲噪声的降噪算法.首先通过分析噪声设计一种提取视频序列背景图像的算法,然后对运动区域采用自适应像素域滤波算法来进行处理.该算法根据最小可觉差和视频图像特征自适应地选择谐波均值滤波、加权算术平均滤波、α-截尾均值滤波和中值滤波.为评估降噪算法性能,将降噪处理前后的视频序列分别进行MPEG-2编码,并改变目标码率对比视频质量.实验结果显示:降噪处理后的视频能够用更少的(约50%)比特数获得相同的主、客观视频质量;或者用相同的比特数获得更高的视频质量.     

基于直方图的自适应图像去噪滤波器

对于那些明显偏离高斯型白噪声的加性噪声,如拖尾脉冲噪声,高斯脉冲噪声等,已有方法的滤噪性能会严重退化.为此,该文提出了一种去除脉冲噪声的新方法.该方法首先由被污染图像估计出原图像的直方图.然后应用模糊集理论,利用加权策略得到了一个符合图像灰度分布统计规律的模糊隶属度函数,以此隶属度函数构建一个加权平均滤波器. 新方法有效地利用了原图像的先验知识,能够根据图像区域特性差异及脉冲噪声强弱自适应地采用不同的滤波尺度.文章比较了传统滤波器、已有的模糊滤波器和本文方法的结果.实验表明本文方法具有更好的效果.     

An Adaptive Radial Basis Function Neural Network Filter for Noise Reduction in Biomedical Recordings

Electroencephalogram (EEG) recordings often experience interference by different kinds of noise, including white, muscle and baseline, severely limiting its utility. Artificial neural networks (ANNs) are effective and powerful tools for removing interference from EEGs. Several methods have been developed, but ANNs appear to be the most effective for reducing muscle and baseline contamination, especially when the contamination is greater in amplitude than the brain signal. An ANN as a filter for EEG recordings is proposed in this paper, developing a novel framework for investigating and comparing the relative performance of an ANN incorporating real EEG recordings. This method is based on a higher-order statistics-based radial basis function (RBF) network. This ANN improves the results obtained with the conventional EEG filtering techniques: wavelet, singular value decomposition, principal component analysis, adaptive filtering and independent components analysis. Average results for the RBF-based method provided a noise reduction (SIR) of (mean\(\pm \) SD) \(\mathrm{SIR}=19.3\pm 0.3\) in contrast to traditional compared methods that, for the best case, yielded \(\mathrm{SIR}=15.2\pm 0.3\). The system has been evaluated within a wide range of EEG signals. The present study introduces a new method of reducing all EEG interference signals in one step with low EEG distortion and high noise reduction.     

RLS和小波在声信号消噪处理中的应用

在仿真的基础上,介绍了RLS自适应滤波器和小波消噪方法的滤波特性以及消噪的处理方法。通过对实际声采集信号的RLS消噪方法,小波消噪方法和综合消噪方法的处理结果,分析了不同类型的信号数据的不同的处理方法,对于特定的数据类型可考虑采用将两者相结合的方法,处理结果令人满意。     

Using Sorted Switching Median Filter to remove high-density impulse noises

We propose a novel Sorted Switching Median Filter (i.e. SSMF) for effectively denoising extremely corrupted images while preserving the image details. The center pixel is considered as “uncorrupted” or “corrupted” noise in the detecting stage. The corrupted pixels that possess more noise-free surroundings will have higher processing priority in the SSMF sorting and filtering stages to rescue the heavily noisy neighbors. Five noise models are considered to assess the performance of the proposed SSMF algorithm. Several extensive simulation results conducted on both grayscale and color images with a wide range (from 10% to 90%) of noise corruption clearly show that the proposed SSMF substantially outperforms all other existing median-based filters.     

基于同态滤波与自适应模糊多级中值滤波级联算法的散斑噪声污染图像恢复

提出了一种用于恢复散斑噪声污染图像的同态滤波与自适应模糊多级中值滤波级联算法 ,计算机仿真实验结果表明它既保持了图像的几何结构 ,又有效地抑制了散斑噪声 ,并且通过比较证明它优于同态滤波与多级中值滤波级联算法     

Least Squares-Based Filter for Remote SensingImage Noise Reduction

The Vondrak filter is a unique technique for smoothing data. The filter aims to achieve a balance between the fidelity and the smoothness of the filtered results. It can therefore preserve the original attributes of the observational data while, at the same time, smooth out the noise. We reformulate the 1-D Vondrak filter that has been widely used in data processing in fields such as astronomy and geophysics and then extend it into two dimensions. The method of conjugate gradients is used to solve the least squares optimization problem. The proposed 2-D filter is a powerful tool for enhancing the quality of various geoscience and remote sensing data such as satellite images. Various tests with simulated and real synthetic aperture radar interferograms show that the new filter is very effective in removing the noise.     

模糊自适应滤波技术在AMT车辆信息处理中的工程应用

准确和快速的信息处理技术是实现车辆起步控制的关键。对于模拟信号，采用常规的在线滤波技术便可获得较理想的效果，但对于转速脉冲信号，因为包含高频过零脉冲，其滤波技术十分困难，为此本文引入模糊推理技术，采用人工智能的方法进行自适应滤波，实验证明，其滤波效果十分明显。     

一种抑制同步开关噪声的改进总线翻转编码方法

提出了一种改进总线翻转编码方法,用于抑制高速集成电路系统中的同步开关噪声.该方法可以显著减少总线平均翻转比特位数,同时尽可能使总线相邻位保持奇模传输,有利于改善信号完整性.利用FPGA实现了提出的改进总线翻转编码模块.物理实验表明,相对总线翻转编码,该方法以功耗稍有增加的代价,可取得平均翻转数量减少15.17%、电源波动噪声减小22.34%的编码增益.     

用于光纤水听器降噪的自适应滤波器

分析了自适应滤波器的原理和算法流程,在Labview软件中采用自适应滤波中的噪声抵消方法对实验中的光纤水听器阵列内的单元数据进行了处理,结果表明在静态目标检测中,可以在不降低信号强度的情况下,将整体噪声水平降低10dB,从而可以得到清晰的阵列波束图;在对拖曳噪声数据的处理中,噪声也得到了明显的抑制。因此,将自适应滤波器用于光纤水听器传感信号的后处理有一定的应用价值。