基于噪声检测的图像去噪算法

提出一种图像去噪算法.首先利用4个方向算子来将图像像素分类成噪声像素和信号像素,然后设计一个基于中值的、权值自适应调整的、加权类型的中值滤波器来去除和恢复检测到的噪声像素,而保留信号像素不变.实验结果表明,新的滤波算法在高效去除冲击噪声的同时还能较好地保护图像细节信息,其滤波性能胜过传统的中值滤波器及其它一些典型的和最近开发的改进型中值滤波器.     

一种基于自适应的新型中值滤波算法

提出了一种新的自适应中值滤波算法,首先使用3×3窗口在图像上滑动,计算该窗口中心像素的块均匀度,并与整幅图像的块均匀度比较,自适应地确定窗口中心像素是否为噪声点;然后统计3×3窗口中噪声点的个数,自适应地调整滤波窗口大小,最后自适应地计算权值,并采用改进的加权中值滤波方法对噪声点进行逐点滤波。该方法既能有效地去除图像噪声点,又能较好地保持图像细节部分。通过对实验结果进一步分析,该方法比均值滤波和中值滤波的性能更加优化,在椒盐噪声大小相同的情况下,PSNR值提高了9.4~12.7。评价结果与目视效果吻合良好,为图像去除噪声提供了一个新的途径。     

一种倒数加权的窗口自适应邻域图像滤波算法

对于叠加了白噪声的图像,提出一种倒数加权的窗口自适应邻域图像滤波算法.算法首先利用自适应邻域统计的概念在以每个滤波点为中心的滤波窗口内,为其建立参与滤波的自适应邻域像素集合,随后对纳入自适应邻域的像素进行倒数加权作为滤波结果.仿真和对比实验的结果显示,提出的算法在性能上超过了传统的中值滤波和窗口自适应邻域滤波算法.它能在有效抑制加性白噪声的同时,完好地保持图像的边界和细节信息,并且滤波后的图像获得了良好的视觉效果.     

一种新型的自适应模糊中值滤波算法

针对传统中值滤波算法不能很好地保护图像细节以及受严重噪声污染时性能急剧下降的情况,提出了一种新型的自适应模糊中值滤波算法。通过比较滤波窗口内像素点的灰度值与像素点灰度值的均值定义了模糊滤波系数,利用此模糊滤波系数对滤波方法进行加权,得到一种加权中值滤波器。通过对小窗口内的灰度值不等于最大灰度值和最小灰度值的像素点的检测自适应调整窗口大小,对超过设定的最大窗口的情况,噪声点的灰度值用四个相邻的已处理的像素点灰度值的均值进行替换。仿真结果表明,新算法具有较好的细节保护能力和较强的去除噪声能力。     

去除椒盐噪声的自适应开关加权均值滤波

提出一种去除椒盐噪声的自适应开关加权均值滤波算法。该算法采用一种新的噪声检测方法将图像中的像素分为信号点和噪声点,对检测出的噪声点采用加权均值滤波进行处理,而信号点保持其灰度值不变直接输出。实验结果表明,该算法能在有效去除椒盐噪声的同时保护图像细节,较传统中值滤波及其改算法有更好的滤波性能。     

核磁共振图像归一化互相关非局部自适应去噪

为了更好地去除核磁共振(MR)图像中莱斯(Rician)分布的噪声,首先提出使用图像局部归一化互相关(NCC)作为几何结构相似性的一个表征,对传统非局部算法中使用灰度计算像素相似性权值的方法进行有效补充;然后,将改进方法分别应用于非局部均值算法和非局部最小线性均方误差估计算法,并根据局部信噪比(SNR)动态自适应地计算非局部算法中待滤波像素自身的加权值或者像素之间相似性阈值,达到对核磁图像自适应降噪的目的。实验结果表明,该算法可以更好地抑制核磁图像中的莱斯噪声,有效保留图像中细节信息,对核磁共振图像进一步的分析研究以及应用于临床诊断等具有非常重要的应用价值。     

加权Myriad滤波器的研究

为了克服在图像处理领域常用的线性滤波器的不足,非线性滤波器就成了非常有意义的一个研究方向。Myriad算法是基于稳定模型的一种非线性滤波算法,它能够充分利用稳定分布的多种模式来进行非线性信号加权处理。Myriad滤波作为一种图像滤波算法,和常用的中值滤波相比,其优势在于不仅能够有效地滤除盐椒噪声,还能够使细节部分保持得更好。本文提出了中心加权Myriad滤波器和自适应加权Myriad滤波器,通过对参数K的调节,平衡在窗口中去除噪声和保持图像细节之间的矛盾,而所加权重也能够根据图像自适应变化。     

图像脉冲噪声滤波算法

针对低噪声污染图像提出了一种改进的中值滤波算法.该算法通过计算滑动窗口内的像素均值和方差,根据数理统计特性,自适应选定阈值,对符合噪声条件的像素进行初次滤除,然后采用开关中值滤波算法对不符合条件的像素再次滤波.实验结果表明,该算法既能有效地去除噪声,又能清晰地保持图像边缘,降低了传统改进型中值滤波算法对阚值的依赖性和对图像边缘细节的损害程度,且滤波性能优于一些典型改进型中值滤波算法.     

CCD扫描噪声建模及自适应滤波算法

为去除图像因扫描引入的电荷耦合器件(CCD)噪声,提出一种基于变窗口的自适应滤波算法。分析CCD主要噪声：散粒,固有和输出噪声的噪声特性,建立CCD扫描噪声模型,根据噪声和边缘处理方式的不同设计了局部和全局自适应滤波器。实验结果表明,该算法具有较好的信噪分离能力,在充分抑制噪声的同时,很好地保持了边缘,提高对比度,视觉效果良好。     

去除红外图像中脉冲噪声的双边加权中值滤波

针对现有方法在去除红外图像的脉冲噪声时,未能有效保持图像的边缘细节和纹理结构,提出了基于统计检测的双边加权中值滤波算法。算法根据脉冲噪声的取值和分布特征,用最小和最大像素值以及统计规律进行噪声检测;对检测出来的噪声像素,以多尺度的方式、自适应地用双边加权系数对邻域中的无噪像素和已经去噪处理的像素进行频次加权,然后取它们的中值作为当前噪声像素的估计值。其中双边加权系数自适应于距离邻近度与灰度相似度。实验结果表明,相对于部分现有方法,所提方法去噪所得的EPI和SSIM值更高,去噪图像的视觉效果更佳。     

基于协同过滤的垃圾邮件过滤系统

针对当前垃圾邮件过滤技术中邮件性质评价难及邮件附件判断难的问题,提出协同过滤模型,设计一个多层次垃圾邮件过滤系统。该系统针对垃圾邮件一般群发给多人的特点,提取用户的操作和阅读速度进行反馈,利用他人的反馈结果进行协同过滤。实验和分析结果表明,协同过滤技术有效地提高了垃圾邮件过滤的召回率。     

信息协同过滤

1.引言网络的迅速发展、信息的日益丰富使得信息过滤越来越重要。在网络发展初期发挥了重大作用的搜索引擎正面临着困境:网络资源的众多和低组织性使得搜索引擎无法准确地根据用户提交的查询返回用户需要的内容。单一的关键词提供的信息量太少,难以据此准确判断用户的需求。而传统的基于内容(关键词匹配)的过滤技术在人工智能自然语言理解没有重大突破之前已很难再有较大的发展,以满足用户的进一步需求。     

垃圾邮件过滤

自从互联网普及以来,电子邮件逐渐成为人们生活中便捷的通信手段之一。但随之产生的垃圾邮件泛滥成灾,污染网络环境,占用大量传输、存储和运算资源,影响了网络的正常运行。垃圾邮件过滤技术逐渐成为信息网络安全研究领域的热点。本文从内容过滤、接入过滤、行为过滤等三方面对垃圾邮件过滤技术的研究现状进行综述。     

Filtering with clouds

Selecting a particular kernel to filter a given digital signal can be a difficult task. One solution to solve this difficulty is to filter with multiple kernels. However, this solution can be computationally costly. Using the fact that most kernels used for low-pass signal filtering can be assimilated to probability distributions (or linear combinations of probability distributions), we propose to model sets of kernels by convex sets of probabilities. In particular, we use specific representations that allow us to perform a robustness analysis without added computational costs. The result of this analysis is an interval-valued filtered signal. Among such representations are possibility distributions, from which have been defined maxitive kernels. However, one drawback of maxitive kernels is their limited expressiveness. In this paper, we extend this approach by considering another representation of convex sets of probabilities, namely clouds, from which we define cloudy kernels. We show that cloudy kernels are able to represent sets of kernels whose bandwidth is upper and lower bounded, and can therefore be used as a good trade-off between the classical and the maxitive approach, avoiding some of their respective shortcomings without making computations prohibitive. Finally, the benefits of using cloudy filters is demonstrated through some experiments.     

Gabor滤波器的快速实现

本文提出了 Gabor 滤波器的两种快速实现方法. 这两种方法首先把 Gabor 滤波器分解为多个不同方向上有着不同参数的一维高斯滤波器的组合, 然后通过递归的方法分别实现这些高斯滤波器, 从而实现 Gabor 滤波器. 实验和分析结果表明, 本文提出的 Gabor 滤波器的快速实现方法, 不论是计算复杂度还是计算精度, 都比基于卷积的标准实现方法有着更好的性能和效果.     

Motion Balance Filtering

This paper presents a new technique called motion balance filtering, which corrects an unbalanced motion to a balanced one while preserving the original motion characteristics as much as possible. Differently from previous approaches that deal only with the balance of static posture, we solve the problem of balancing a dynamic motion. We achieve dynamic balance by analyzing and controlling the trajectory of the zero moment point (ZMP). Our algorithm consists of three steps. First, it analyzes the ZMP trajectory to find out the duration in which dynamic balance is violated. Dynamic imbalance is identified by the ZMP trajectory segments lying out of the supporting area. Next, the algorithm modifies the ZMP trajectory by projecting it into the supporting area. Finally, it generates the balanced motion that satisfies the new ZMP constraint. This process is formulated as a constrained optimization problem so that the new motion resembles the original motion as much as possible. Experiments prove that our motion balance filtering algorithm is a useful method to add physical realism to a kinematically edited motion.     

Multiplierless Adaptive Filtering

Bose, T., Venkatachalam, A., and Thamvichai, R., Multiplierless Adaptive Filtering, Digital Signal Processing12 (2002) 107–118When digital filters are designed with power-of-2 coefficients, the multiplications can be implemented by simple shifting operations. For VLSI implementations, multiplierless filters are faster and more compact than filters with multipliers. In this paper, an algorithm for finding and updating the power-of-2 coefficients of an adaptive filter is designed. The new method uses the well-known Genetic Algorithm (GA) for this purpose. The GA is used in a unique way in order to reduce computations. Small blocks of data are used for the GA and only one new generation is produced per sample of data. This, coupled with the fact that the coefficients are power-of-2, yields a computational complexity of O(N) additions and no multiplications. The algorithm is investigated for applications in adaptive linear prediction and system identification. The results are very promising and illustrate the performance of the new algorithm.     

Coherence-Enhancing Diffusion Filtering

The completion of interrupted lines or the enhancement of flow-like structures is a challenging task in computer vision, human vision, and image processing. We address this problem by presenting a multiscale method in which a nonlinear diffusion filter is steered by the so-called interest operator (second-moment matrix, structure tensor). An m-dimensional formulation of this method is analysed with respect to its well-posedness and scale-space properties. An efficient scheme is presented which uses a stabilization by a semi-implicit additive operator splitting (AOS), and the scale-space behaviour of this method is illustrated by applying it to both 2-D and 3-D images.     

网络过滤研究

介绍一种基于Web挖掘和URL相结合的Web过滤方法，利用Web挖掘实现基于内容的离线Web分类，有效地解决了单纯基于关键词过滤和人工维护URL过滤系统的缺陷。实验结果表明，该系统对于网页类别的识别达到了可以接受的程度，具有良好的实用价值。