Adaptive Gaussian Noise Image Removal Algorithm Using Filtering-Based Noise Estimation

This paper proposes a spatially denoising algorithm using filtering-based noise estimation for an image corrupted by Gaussian noise.The proposed algorithm consists of two stages:estimation and elimination of noise density.To adaptively deal with variety of the noise amount,a noisy input image is firstly filtered by a lowpass filter.Standard deviation of the noise is computed from different images between the noisy input and its filtered image.In addition,a modified Gaussian noise removal filter based on the local statistics such as local weighted mean,local weighted activity and local maximum is used to control the degree of noise suppression.Experiments show the effectiveness of the proposed algorithm.     

数字超声无损评价系统中的脉冲噪声

在用数字超时接接头评价时发现,噪声是微弱超声信号检测的主要障碍。建立数字超声系统的物理模型,分析声学噪声和非声学噪声,提出消除脉总噪声的极值滤波算法。实验证明,该算法简单高效,能有效地去除脉冲噪声,且保持领事的有用分量不受滤波影响。     

Automatic estimation and removal of noise on digital image

An spatially adaptive noise detection and removal algorithm is proposed.Under the assumption that an observed image and its additive noise have Gaussian distribution,the noise parameters are estimated with local statistics from an observed degraded image,and the parameters are used to define the constraints on the noise detection process.In addition,an adaptive low-pass filter having a variable filter window defined by the constraints on noise detection is used to control the degree of smoothness of the reconstructed image.Experimental results demonstrate the capability of the proposed algorithm.     

一种有效的去除图像混合噪声的滤波算法

依据噪声特点以及图像的像素关联性,提出了一种有效的数字图像混合噪声滤波算法。该算法首先对图像像素进行检测,依据受脉冲噪声污染的图像像素与其周围邻域多数像素在亮度上具有显著差异的特点准确检测出脉冲噪声,然后以检测到的脉冲噪声为被处理像素,用其邻域内未被脉冲噪声污染的图像像素对其进行中值滤波,由于当前脉冲噪声点以及邻域脉冲噪声点均未参与滤波运算,从而较好地保护了图像的细节。对图像中的高斯噪声,提出了一种改进的加权均值滤波算法,该算法在定义相关度函数时,既考虑了像素的灰度相关性,又考虑了像素的位置相关性。实验结果表明:提出的混合噪声滤波算法不仅可以有效滤除图像中的混合噪声,而且还可以较好地保护图像的细节。     

矿用低噪局部通风机设计中的降噪方法研究

对风机设计中的降噪方法进行了研究，并应用于自行研制的矿用子午加速局部通风机中，通过实验证明，以此方法设计的风机与相同转速和直径的局部风机相比，降噪效果较好。     

基于二进小波和抗噪形态学的烟雾边缘检测算法

针对枪口烟雾图像的不规则性以及烟雾扩散速度快等特点,传统的边缘检测算法无法高效地提取烟雾边缘轮廓的问题,对烟雾图像采集技术、烟雾图像预处理技术以及烟雾图像边缘检测技术进行了研究,提出了一种改进的二进小波和抗噪形态学融合的边缘检测算法.首先,在 B 样条二进小波基础上,将二进小波消失矩的阶数提高到四阶;其次,选取方向不同的结构元素,得出改进的形态学算子;最后,用小波逆变换重新构造枪口烟雾图像,对其进行锐化处理,输出边缘信息.仿真结果表明,该算法检测出来的枪口烟雾图像边缘定位准确且清晰完整,能有效抑制噪声,在客观方面优于传统的边缘检测算法.     

传感器网络中基于相关性的协同目标检测算法

目标检测是传感器网络的重要应用方向之一,也是对目标进行定位、跟踪的基础和前提。现有的目标检测算法大多属于局部判决融合算法,对噪声干扰的影响考虑较少,在检测性能方面存在不足。提出了一种基于相关性的协同目标检测算法,各传感器节点将一小段时间内的测量值序列发送给局部中心节点,构成一个检测矩阵;局部中心节点对检测矩阵中列向量的相关性进行计算和评估,从而判定目标是否存在。仿真实验和应用验证的结果表明,该算法能够很好地抑制噪声干扰的影响,检测结果的准确性较高。     

航空发动机轴承噪声检测技术分析研究

针对因轴承噪声超标而返厂发动机增多且诊断准确率难以保证的问题,介绍了轴承振动与噪声的特性和轴承噪声产生的原理,分析了影响轴承噪声检测准确性的因素,提出了在轴承制造、发动机装配、轴承噪声检测等环节加以改善的措施。     

基于遗传算法的低噪声齿轮传动设计

用遗传算法进行了低噪声齿轮传动参数的优化设计，目标函数为啮合传动的冲击速度加权函数，约束函数为齿轮传动设计中的常用约束条件，数值计算结果与已有结果比较表明新方法可行。     

Noise control technology for generator sets in enclosures

Currently, noise pollution is an environmental problem all over the world. The health and life of human beings are affected by loud noise from high power generator sets. To reduce such noise, a sound-attenuated enclosure is widely used for its high performance and convenient usage. By installing equipment in an enclosure, noise is controlled and prevented from radiating. In this paper, noise control techniques for enclosures are presented. Enclosure development trends are predicted.