有源抗噪声护耳器H2/H∞优化方法研究

采用固定系数滤波器和自适应滤波器相结合来实现一种有源抗噪声护耳器系统。固定系数滤波器除了降低宽带噪声,其最主要的作用在于减小次级通道的不确定性。固定系数滤波器和次级通道滤波器都采用H_2/H_∞优化方法设计得到。仿真和实验结果表明:固定系数滤波器提高了自适应算法的稳定性,护耳器系统在宽带和周期性噪声环境中都取得了比较好的降噪效果。     

时域递归滤波对微光成像视距影响的研究

 针对微光成像中噪声较大及视距较短的问题,提出了一种自适应时域递归滤波算法。该算法通过自动调节时域递归的滤波系数来提高信噪比和延伸视距。实验显示当滤波系数分别为0.50、0.75和0.875时,视距分别能延伸至原始的1.73倍、2.64倍和3.87倍,所得到的视距延伸与理论值基本保持一致。实验结果表明该算法在保持图像运动部分清晰的同时,还能有效地消除噪声并延伸微光成像系统的视距。     

基于小波变换和维纳滤波的半导体器件1/f噪声滤波

针对半导体器件中普遍存在的1/f噪声提出了一种结合了提升小波变换和维纳滤波器的处理方法.首先利用重新加权迭代最小二乘法拟合1/f噪声的功率谱曲线得到噪声参数的估计,从而选择恰当的小波.其次,对包含了1/f噪声的信号进行提升小波变换.考虑到小波变换对1/f噪声的白化作用,利用维纳滤波器对每一层小波系数进行处理.设计了最优全通滤波器以校正维纳滤波器的相频特性,使得小波系数经滤波后相位不变.最后利用提升小波逆变换获得被1/f噪声淹没的信号.利用实验检验了提出方法的有效性,实验数据采自用于微创外科手术机器人的力传感器.结果表明提出的方法能够有效抑制1/f噪声,并使传感器的分辨力提高了25%. 关键词： 半导体器件 f噪声')" href="#">1/f噪声 提升小波变换 维纳滤波     

改进维纳滤波器及其在目标方位估计中的应用

针对复杂的水声环境以及信噪比较低的目标信号导致方位估计性能较差的问题,本文提出了一种基于改进维纳滤波器和波束形成器的方位估计方法,该方法能够抑制噪声,提高目标方位估计性能。首先利用改进维纳滤波器抑制各通道接收数据中的噪声,提高输出信噪比。在此基础上,将改进维纳滤波器的输出通过波束形成器,获得目标的方位估计。改进维纳滤波器能够通过调整滤波器参数,控制滤波器的噪声抑制能力和信号失真。因此,针对不同的波束形成器对信号失真的敏感程度不同,可以通过调节改进维纳滤波器的参数,获得噪声抑制与信号失真之间的最佳折中,从而提高输出信噪比,降低目标方位估计的信噪比门限和均方根误差。仿真和实验结果验证了本文方法。      

基于长周期光纤光栅滤波器的掺铒光纤放大器理论和实验研究

从理论和实验上研究了带有高频二氧化碳激光写入的低成本长周期光纤光栅（LPFG）掺铒光纤放大器（EDFA）.结果表明,单波长和多波长EDFA的性能都可以通过在掺铒光纤（EDF）中插入长周期光纤光栅用作自发辐射噪声（ASE）滤波器或增益平坦器来提高性能.优化设计了带LPFG噪声滤波器的线放EDFA,与没有LPFG噪声滤波器相比,线放的噪声和小信号增益分别被减小和提高了约0.5 dB和7 dB。通过在多波长EDFA的EDF中插入一个LPFG增益平坦滤波器的方法,获得了1.5 dB的增益平坦度,与没有LPFG平坦器相比,EDFA的噪声被减小了0.1 dB,增益被提高了1 dB.     

层析三维数字化仪层析图像滤波器的设计及研究

提出一种新型的递归中值滤波器，抛掉了统计参数的制约，将滤波算法转化为一种优化处理。该方法兼顾了滤波处理的光滑连续性及抑制噪声的累积特性，可有效地消除脉冲型干扰的影响，同时也从理论的角度上对该算法进行了分析。为消除加性高斯噪声，提出了一种基于图像边缘方向的小波线性滤波器，它仅仅处理边缘信息。该算汉的极大优点是克服了边缘模糊效应，小波的去噪逆向重构的处理方法对边缘为跃型的层析图象非常实用。     

自适应滤波器的设计与制作

自适应滤波器是一种能够根据噪声特性实时修改自身参数,从而达到最佳滤波效果的滤波器,目前广泛应用于数字信号处理的各个领域。设计了一款完整的自适应滤波器展示装置,首先使用加法器和移相器电路对原始信号进行加噪处理,将加噪后的信号和原始噪声经过模数(AD)转换后输入FPGA,并在FPGA平台上构建了基于最小均方误差(LMS)算法自适应滤波器,最后将滤波器输出的信号经过数模(DA)转换后在示波器上进行观察。实验结果表明,该自适应滤波方案能在1-200KHz的频带范围内有效地滤除与原始信号频率差大于10Hz的正弦波、三角波和高斯噪声等噪声信号。     

基于邻域特征匹配的通用噪声滤波器

图像去噪是遥感图像复原的重要步骤。在去除图像噪声的同时希望尽可能多地保留图像的纹理细节信息。受较差的成像环境和图像数据远距离传输的影响,遥感图像中一般都含有较强的高斯-脉冲混合噪声,而在现有的图像去噪算法中,能够同时去除图像中的高斯-脉冲混合噪声的通用噪声滤波器很少。以非局部平均方法的滤波思想为基础,通过引入邻域相似度评价的概念和脉冲噪声探测器,提出了基于邻域特征匹配的通用噪声滤波器。实验结果表明:基于邻域特征匹配的通用噪声滤波器具备有很好地去除图像高斯-脉冲混合噪声的能力,在去除高斯-脉冲混合噪声的同时能够很好地保持图像的复杂纹理和精细细节,并且便于向DSP/FPGA多处理器平台上移植。     

一种尺度自适应调整的高斯滤波器设计方法

固定尺度参数的经典高斯滤波器往往在滤除噪声的同时造成图像的模糊,为此设计了一种尺度可变的自适应高斯滤波器。通过计算滤波器各滤波窗口内像素点灰度值的均值,以及该均值与当前像素点灰度值的差值,确定滤波窗口的平滑度,并将其作为高斯函数尺度的大小,从而实现滤波器尺度参数的自适应调整。实验结果表明,该滤波器在有效滤除噪声的同时能够尽可能的保持图像原有信息不受影响,且计算简单,适于工程应用。     

用数字滤波消除散斑条纹图噪声

本文讨论了散斑摄影条纹图的噪声来源及模型,设计合适的数字滤波器.采取正交实验手段,全面分析了噪声、条纹对比度和密度对条纹方向及间距测量精度的影响.     

闪光照相CCD图像的自适应中值滤波方法

中值滤波是一种在去除噪声的同时能较好地保护图像边缘细节的非线性图像处理方法。为了滤除闪光照相CCD图像中的脉冲噪声，同时能更好地保护图像边缘，提出了一种改进的自适应中值滤波方法。该方法采用局部中值和局部方差作为判断噪声点的阈值，实现了局部自适应的中值滤波，克服了传统自适应中值滤波方法的缺点，对椒盐噪声和随机脉冲噪声均有较好的滤波效果。实验结果表明，该方法消除图像脉冲噪声十分有效，对闪光照相CCD图像的处理结果也较好。     

自适应中值-加权均值混合滤波器

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。该方法先将图像分为若干区域,并对每个区域进行噪声检测以实现两类噪声的分离,然后再分别采用自适应中值滤波和自适应加权均值滤波将分离出的脉冲噪声和高斯噪声去除。对这种新方法进行了计算机模拟实验。结果表明:新方法较前人提及的三种混合滤波方法具有更优的滤波性能,在有效抑制混合噪声的同时能很好地保护图像中的细节,为消除图像中的混合噪声提供了一种有效的途径。     

基于中值滤波和提升小波分析的图像去噪方法研究

针对现有算法大多对单一高斯噪声或脉冲噪声进行图像滤波的问题,在对二维图像平滑去噪的过程中,采用基于中值滤波和提升小波变换相结合的图像去噪方法。在中值滤波基础上,构造基于脉冲检测的中值滤波器,找出混合噪声中脉冲噪声并进行滤波;与此同时,对原始小波进行提升,构造提升小波,然后采用提升小波阈值去噪方法抑制高斯噪声。实验结果表明:采用本文方法,混合噪声得到有效抑制,去噪效果好。     

Modifying NL-means to a universal filter

Despite a state-of-the-art filter for removing Gaussian noise, non-local means filter (NLM), like its local counterpart (the mean filter), is no longer so effective in removing salt-pepper noise which is common in real world as well. By contrast, adaptive median filter (AMF) is concise and can remove this type of noise effectively. Inspired by the AMF filtering strategies, in this paper, we modify NLM to a novel non-local universal filter (UNLM) which can remove not only either of Gaussian noise and salt-pepper noise but also their mixture. Experiments on artificial and benchmark images validate its feasibility and effectiveness.     

Decision-based adaptive morphological filter for fixed-value impulse noise removal

A novel adaptive switching morphological filter for removing fixed-value impulse noise is proposed. The proposed filter firstly identifies noise pixels using the two-stage morphological noise detector, in which the initial noise detection is used to identify the noise candidates based on the morphological gradients and the refined noise detection based on the combined conditional morphological operators is adopted to further classify the noise candidates as the noise pixels or noise-free pixels. Then the detected noise pixels are removed by the adaptive morphological filter using the conditional rank-order morphological operators while the noise-free pixels are left unaltered. Extensive simulations show that the proposed filter outperforms a number of existing switching-based filters because of its excellent performance in terms of noise detection and image restoration.     

Statistical properties of polarization image and despeckling method by multiresolution block-matching 3D filter

The theoretical and experimental investigations on the polarization imagery system of speckle statistical characteristics and speckle removing method are researched. A method to obtain two images encoded by polarization degree with a single measurement process is proposed. A theoretical model for polarization imagery system on Müller matrix is proposed. According to modern charge coupled device (CCD) imaging characteristics, speckles are divided into two kinds, namely small speckle and big speckle. Based on this model, a speckle reduction algorithm based on a dual-tree complex wavelet transform (DTCWT) and blockmatching 3D filter (BM3D) is proposed (DTBM3D). Original laser image data transformed by logarithmic compression is decomposed by DTCWT into approximation and detail subbands. Bilateral filtering is applied to the approximation subbands, and a suited BM3D filter is applied to the detail subbands. The despeckling results show that contrast improvement index and edge preserve index outperform those of traditional methods. The researches have important reference value in research of speckle noise level and removing speckle noise.     

An MRI denoising method using image data redundancy and local SNR estimation

This paper presents an LMMSE-based method for the three-dimensional (3D) denoising of MR images assuming a Rician noise model. Conventionally, the LMMSE method estimates the noise-less signal values using the observed MR data samples within local neighborhoods. This is not an efficient procedure to deal with this issue while the 3D MR data intrinsically includes many similar samples that can be used to improve the estimation results. To overcome this problem, we model MR data as random fields and establish a principled way which is capable of choosing the samples not only from a local neighborhood but also from a large portion of the given data. To follow the similar samples within the MR data, an effective similarity measure based on the local statistical moments of images is presented. The parameters of the proposed filter are automatically chosen from the estimated local signal-to-noise ratio. To further enhance the denoising performance, a recursive version of the introduced approach is also addressed. The proposed filter is compared with related state-of-the-art filters using both synthetic and real MR datasets. The experimental results demonstrate the superior performance of our proposal in removing the noise and preserving the anatomical structures of MR images.     

模糊权值中值滤波的X射线图像消噪算法

针对X射线荧光图像的低亮度及噪音造成的对比度差和图像模糊的问题,提出了一种模糊权值中值滤波的图像消噪算法.先用模糊邻域检测法结合梯度检测法分离原始图像中的噪音点与非噪音点,然后在噪音点的邻域内,计算各像素点与邻域中值的模糊相似度,用相似度作中值的权值,对噪音点邻域进行加权滤波|这种算法使图像的非噪音点保持不变.实验结果表明, 本文算法不仅具有较强的消噪能力,而且能够保持图像的边缘细节和纹理信息.     

便携式X光机图像降噪复合算法研究

便携式X光机应用越来越广,因而对其所成图像的降噪也显得尤为重要.本文首先讨论和分析了便携式X光机成像系统噪声的来源及其特性,针对传统单一降噪算法存在的不足,提出了一种新的复合式降噪算法.该复合算法不仅对高斯噪声和脉冲噪声有很好的滤除效果,同时也能有效地保护图像的细节部分.仿真实验证明,该算法切实可行.