一种改进的自适应中值滤波算法

传统的自适应中值滤波算法,利用极值判别像素点是否为噪声点。该方法容易将边缘点误判为噪声点,将噪声点误判为信号点。本文针对这一问题,提出一种利用边缘点与噪声点的差异判别噪声点,并将噪声点分为平滑区噪声点与边缘区域噪声点,对不同类型噪声点进行不同处理。从而达到更好的抑制噪声与保护图像细节效果。     

基于直方图统计信息的斑点噪声参数盲估计

以常见的斑点噪声为研究对象提出一种简单、快速的图像斑点噪声参数盲估计方法。该方法通过在仿真图像中加入不同强度的斑点噪声,分析含噪图像均匀区域内直方图分布特点,构造反映图像斑噪强度的噪声特征值,建立噪声强度与噪声特征值之间映射函数。实验结果显示,该函数不需要任何先验知识即可快速、有效地估计图像中的斑噪强度,可用于估计图像获取或传输时的噪声环境、分析斑点噪声强度与图像质量优劣的关系、指导及修改现有抑噪算法设计。     

卡尔曼滤波系统和量测噪声自适应估计的关联性

卡尔曼滤波是惯导系统(INS)/GPS组合导航的主要算法之一,Sage-Husa算法是在卡尔曼滤波基础上,为减少系统噪声和量测噪声的不确定性对误差估计的影响而采用的自适应估计方法.对Sage-Husa算法提出了4条改进措施;并通过在3种数据扰动情形下的仿真计算发现,只对一类噪声做自适应估计更容易产生较大的偏差,对系统噪声和量测噪声两类噪声同时做自适应估计,其效果要优于只对一类噪声做自适应估计,把此现象定义为卡尔曼滤波的系统和量测噪声自适应估计的关联性.这个结果不同于一些文献的观点.此项研究对自适应卡尔曼滤波在INS/GPS组合导航的工程化应用有较高的实用价值.     

Tracking of Nonstationary Noise Based on Data-Driven Recursive Noise Power Estimation

This paper considers estimation of the noise spectral variance from speech signals contaminated by highly nonstationary noise sources. The method can accurately track fast changes in noise power level (up to about 10 dB/s). In each time frame, for each frequency bin, the noise variance estimate is updated recursively with the minimum mean-square error (mmse) estimate of the current noise power. A time- and frequency-dependent smoothing parameter is used, which is varied according to an estimate of speech presence probability. In this way, the amount of speech power leaking into the noise estimates is kept low. For the estimation of the noise power, a spectral gain function is used, which is found by an iterative data-driven training method. The proposed noise tracking method is tested on various stationary and nonstationary noise sources, for a wide range of signal-to-noise ratios, and compared with two state-of-the-art methods. When used in a speech enhancement system, improvements in segmental signal-to-noise ratio of more than 1 dB can be obtained for the most nonstationary noise sources at high noise levels.     

Intelligibility of synthesized voice messages in commercial truck cab noise for normal-hearing and hearing-impaired listeners

A human factors experiment was conducted to assess the intelligibility of synthesized speech under a variety of noise conditions for both hearing-impaired and normal-hearing subjects. Modified Rhyme Test stimuli were used to determine intelligibility in four speech-to-noise (S/N) ratios (0, 5, 10, and 15 dB), and three noise types, consisting of fiat-by-octaves (pink) noise, interior noise of a currently produced heavy truck, and truck cab noise with added background speech. A quiet condition was also investigated. During recording of the truck noise for the experiment, in-cab noise measurements were obtained. According to OSHA standards, these data indicated that drivers of the sampled trucks have a minimal risk for noise-induced hearing loss due to in-cab noise exposure when driving at freeway speeds because noise levels were below 80 dBA. In the intelligibility experiment, subjects with hearing loss had significantly lower intelligibility than normal-hearing subjects, both in quiet and in noise, but no interaction with noise type or S/N ratio was found. Intelligibility was significantly lower for the noise with background speech than the other noises, but the truck noise produced intelligibility equal to the pink noise. An analytical prediction of intelligibility using Articulation Index calculations exhibited a high positive correlation with the empirically obtained intelligibility data for both groups of subjects.     

一种新的基于噪声点检测的脉冲噪声去噪算法

中值滤波是广泛应用于去除脉冲噪声的一种非线性去噪方法,但是单一地使用中值滤波方法去除脉冲噪声会造成图像细节信息的丢失,从而使图像变得模糊。基于噪声点检测的脉冲噪声滤波方法可以在滤除噪声的同时有效地保持图像的细节信息。该文在此基础上提出了一种新的基于噪声点检测的脉冲噪声滤波算法,该算法在检测噪声点时用被检测点的中值滤波结果作为判定该点是否为噪声点的依据。而在滤除被检测到的噪声点时,采用的是迭代的中值滤波算法。从实验结果中可以看到,与其它中值滤波算法相比,该文的算法在去除脉冲噪声时能取得较好的效果。     

脉冲噪声环境下基于卡尔曼滤波的语音增强

语音增强的目标在于从含噪信号中提取纯净语音,纯净语音在某些环境下会被脉冲噪声所污染,但脉冲噪声的时域分布特征却给语音增强带来困难,使传统方法在脉冲噪声环境下难以取得满意效果。为在平稳脉冲噪声环境下进行语音增强,提出了一种新方法。该方法通过计算确定脉冲噪声样本的能量与含噪信号样本的能量之比最大的频段,利用该频段能量分布情况逐帧判别语音信号是否被脉冲噪声所污染。进一步地,该方法只在被脉冲噪声污染的帧应用卡尔曼滤波算法去噪,并改进了传统算法执行时的自回归(AR)模型参数估计过程。实验中,采用白色脉冲噪声以及有色脉冲噪声污染语音信号,并对低输入信噪比的信号进行语音增强,结果表明所提出的算法能显著地改善信噪比和抑制脉冲噪声。     

HgCdTe轴温探测器噪声的温度特性研究

针对HgCdTe列车轴温探测器,通过测量不同温度下其噪声功率谱的变化,研究了温度对器件噪声的影响。实验结果表明：在-30-20℃范围内,当温度降低时,探测器噪声显著增加,最大增幅分别达到2．7倍（偏流为1mA时）和3．6倍（偏流为2mA时）。经过理论分析发现,探测器热噪声对总噪声的贡献很小,温度变化的主要影响是器件的产生一复合噪声和1／f噪声。     

一种基于噪声拓扑结构的滤波算法

基于脉冲噪声的特点,提出了一种新的非常有效的脉冲噪声的滤波算法。该算法将滤波过程分为两步进行,即第1步对图像的脉冲噪声点进行标识,第2步再对标识的噪声点进行滤波。在第1步这中,充分考虑到脉冲噪声的特点,主要利用了噪声的拓扑连通性;在第2步时,利用噪声点周围非噪声点的信息,来对噪声点进行修复。最后进行了仿真试验,并与传统中值滤波算法和开关中值滤波算法进行了比较,试验表明,在信噪比和细节保留方面,该算法要明显优于它们,特别是对高强度的脉冲噪声也有比较好的效果。     

Image restoration in the presence of impulse noise by adaptive equidistant median filter

After widely studying the methods in literatures for impulse noise removal, aiming at overcoming their deficiencies and further improving the denoising performance, we propose an adaptive equidistant median filter for image restoration in the presence of impulse noise. As an improved and effective alternative to the square neighborhood, the circular neighborhood is proposed for noise detection and removal processing. A noise detector based on adaptive local statistics is proposed, followed by a noise removal technique gaining support from adaptive equidistant median proposed subsequently. Furthermore, the noise removal processing is performed adaptively so as to be robust for various noise densities. Experimental results have shown that the proposed method has substantially improved the performance in noise detection and removal, and is superior than the state-of-the-art filters with excellent capability of noise removal and structural information preservation.

     

空间有色噪声背景下多目标检测性能研究

重点对一些典型的多目标检测方法在空间有色噪声背景下的检测性能进行分析,并利用统一的仿真模型对它们的检测能力进行比较。每种方法都运用了两个分离的线列阵,来接收多个从不同方向入射的平面波和噪声。仿真采用ARMA模型来产生空间有色噪声,使噪声功率谱相似于实际工程应用中的噪声特性。并且分别研究了各种方法的优缺点,对比了这些方法在有色噪声背景下检测信号源数目的效果。     

基于POCS算法的图像超分辨率重建

传统POCS算法对图像进行超分辨率重建时,一般都假设所处理的噪声为零均值的加性高斯白噪声,当噪声为非高斯噪声如椒盐噪声时,POCS算法的重建效果将会下降.针对这一问题,本文对含噪图像首先采用平稳离散小波变换技术进行去噪预处理,然后再用POCS算法重建图像.实验证明,此方法对信噪比较低的图像有很好的重建效果,对高斯及椒盐等噪声处理比较有效.     

某民用直升机舱内噪声水平仿真分析研究

声学仿真分析是进行直升机舱内降噪设计的有效技术手段,良好的降噪设计有利于提升民用直升机的市场竞争力。结合试验数据和统计能量法分析了某民用直升机的舱内噪声源贡献度,进而采用声学边界元法分析了该型机的舱内噪声水平。研究表明,该型机舱内主要噪声源为：主减振动、发动机振动、主减空间辐射声、发动机空间辐射声和油箱舱空间辐射声,在无内饰状态下人耳敏感频率范围内的舱内场点噪声为129 dB,蒙皮、整流罩和挡板是影响舱内噪声水平的关键结构,在考虑内饰材料后,场点噪声最大可下降5 dB。该分析思路可以为直升机舱内降噪设计提供技术支持。     

含特殊噪声模糊图像复原技术的研究及应用

为解决模糊图像复原技术经典算法受噪声等高频成分影响较大的问题,文中提出一种简单快速处理含特殊噪声模糊图像的方法。当噪声叠加到图像中,图像赖以估计模糊核参数的频域特征减弱甚至消失。一般去除噪声的方法在滤除噪声的同时也除去了一些可用于模糊参数估计的重要信息,因此,含噪图像通常会寻求它法处理。但文中研究发现,对于某种特殊的噪声例如椒盐噪声,使用针对于它的滤波方法,例如中值滤波,信息损失量极小,因此含特殊噪声图像可以按此方法处理。结合有针对性的滤波方法去除特殊噪声,减少信息损失,从而快速恢复图像。仿真实验结果表明,对于含噪图像,该算法比以往算法更优越。     

机场噪声实时监测系统的设计与应用

机场噪声对周边社区居民的健康生活影响越来越突出，解决噪声问题首先要对飞机噪声进行监测。机场噪声实时监测系统采用双核 24 位Δ-Σ方式的 AD 采集技术，利用 DSP 的计算能力，实现飞机噪声数据的高速采集和实时计算。利用计算得到的时间-声级曲线等参数识别飞机噪声事件，并将声暴露级、声压等参数通过网络发送到云端进行处理，得到有利于机场噪声管理所需参考文件。     

基于噪声被掩蔽概率的语音增强算法

针对MMSE方法语音失真较大的缺点,提出一种将噪声被掩蔽概率引入高分辨率掩蔽感知模型的方法,通过初始噪声序列进行噪声谱的更新,然后计算噪声掩蔽参数,适时更新数据参数以动态确定每一帧的权值,实验结果表明,该方法在有效抑制背景噪声的同时还降低了音乐噪声,在语音降噪方面实现了比MMSE方法更好的增强效果.     

CMOS图像传感器的自适应降噪方法研究

提出了一种用于CMOS图像传感器的新型自适应降噪方法,并进行了逻辑电路实现。该方法通过运动检测和边缘检测技术进行噪声功率统计和分析,选择性的利用中值滤波、均值滤波以及运动自适应滤波方法,对传感器输出图像进行了数字降噪处理。实验表明本文方法降低了高斯噪声和椒盐噪声的影响,有效提高了图像质量和峰值信噪比。其结构易于电路实现,适用于CMOS图像传感器内部的实时降噪处理。     

Marginal noise removal of document images

Marginal noise is a common phenomenon in document analysis which results from the scanning of thick documents or skew documents. It usually appears in the front of a large and dark region around the margin of document images. Marginal noise might cover meaningful document objects, such as text, graphics and forms. The overlapping of marginal noise with meaningful objects makes it difficult to perform the task of segmentation and recognition of document objects. This paper proposes a novel approach to remove marginal noise. The proposed approach consists of two steps which are marginal noise detection and marginal noise deletion. Marginal noise detection will reduce an original document image into a smaller image, and then find marginal noise regions according to the shape length and location of the split blocks. After the detection of marginal noise regions, different removal methods are performed. A local thresholding method is proposed for the removal of marginal noise in gray-scale document images, whereas a region growing method is devised for binary document images. Experimenting with a wide variety of test samples reveals the feasibility and effectiveness of our proposed approach in removing marginal noises.     

Improving Gabor noise

We have recently proposed a new procedural noise function, Gabor noise, which offers a combination of properties not found in the existing noise functions. In this paper, we present three significant improvements to Gabor noise: 1) an isotropic kernel for Gabor noise, which speeds up isotropic Gabor noise with a factor of roughly two, 2) an error analysis of Gabor noise, which relates the kernel truncation radius to the relative error of the noise, and 3) spatially varying Gabor noise, which enables spatial variation of all noise parameters. These improvements make Gabor noise an even more attractive alternative for the existing noise functions.