Adaptive Fuzzy Morphological Filtering of Impulse Noise in Images

In this paper we first introduce a neural network implementationfor fuzzy morphological operators, and by means of a trainingmethod and differentiable equivalent representations for theoperators we then derive efficient adaptation algorithms to optimizethe structuring elements. Thus we are able to design fuzzy morphologicalfilters for processing multi-level or binary images. The convergencebehavior of basic structuring elements and its significance forother structuring elements of different shape is discussed. Besidesthe filter design, the localized structuring elements obtainedfrom the training method give a structural characterization ofthe image which is useful in many applications. The performanceof the fuzzy morphological filters in removing impulse noisein multi-level and binary images is illustrated and comparedwith existing procedures.     

一种针对图像脉冲噪声的改进中值滤波算法

针对中值滤波算法在图像脉冲噪声处理中存在的不足,提出一种新的改进中值滤波算法.该方法根据噪声图像的极值和像素点滤波窗口的局部信息对滤波窗口内像素点(含待处理像素点)是否为噪声点进行判断,剔除滤波窗口内的噪声点,然后根据新的滤波窗口及待滤波的中心像素点灰度值信息进行滤波操作.以迭代的方法更新噪声图像中的每个像素点,从而去除图像中的脉冲噪声.实验结果表明,与传统中值、加权中值、多级中值滤波方法相比,该方法能有效去除图像中的脉冲噪声,并保持图像细节特征完整.     

Real-Time Hadamard Transform Coding for TV Signals

Analog and digital schemes for implementing the onedimensional Hadamard transform in real time for TV signals has been proposed. Within practical limitations, hardware has been developed and tested according to the scheme. The evaluation of the hardware has been carried out using a real image. Furthermore, bandwidthreduction experiments are conducted for various bit rates. Analog and digital transform coding schemes are compared for prominent performance parameters. It is demonstrated that good broadcast and video-phone quality pictures can be obtained using the first four coefficients, and the first two coefficients, respectively.     

Parameter Estimation for an Adaptive Instrumentation of Hall's Optimum Receiver for Digital Signals in Impulse Noise

Newton's method for root finding is shown to be an effective algorithm for computing maximum likelihood estimates of the bias parameter in Hall's optimum receiver for digital singals in impulse noise. Use of a bias estimator allows the receiver to be adaptively instrumented. A simulation indicates that the number of independent samples of the impulse noise, as modeled by Hall, should be around 20 000 for satisfactory parameter estimates.     

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.     

Real-Time Numerical Filtering of Physiological Signals

The minimization of the sampling rate necessary to store a signal frequently requires filtering of unwanted higher frequency components in order to avoid aliasing errors. In many physiological situations the desired cutoff frequency is too low to be realized by a practical passive analog filter. In such a case either an active analog filter may be used, or the signal may be initially sampled at a higher rate to avoid aliasing, then numerically filtered in real-time, and the resulting smoothed signal sampled at a lower rate (the effective sampling frequency). The purpose of this communication is to describe the use of a class of low-pass digital filters which we have found useful for this purpose.     

Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction

This letter presents a novel two-stage noise adaptive fuzzy switching median (NAFSM) filter for salt-and-pepper noise detection and removal. Initially, the detection stage will utilize the histogram of the corrupted image to identify noise pixels. These detected “noise pixels” will then be subjected to the second stage of the filtering action, while “noise-free pixels” are retained and left unprocessed. Then, the NAFSM filtering mechanism employs fuzzy reasoning to handle uncertainty present in the extracted local information as introduced by noise. Simulation results indicate that the NAFSM is able to outperform some of the salt-and-pepper noise filters existing in literature.      

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.     

嵌入式系统实时中值滤波的高效实现

为了满足嵌入式系统实时数字滤波的需要,针对抗脉冲干扰能力较好的中值数字滤波,提出一种存储量小、运算速度快的高效算法.该算法利用循环存储结构,在存储实时新数据的同时,自动剔除最老的旧数据,释放其所占用的存储资源,避免为新到来的数据申请存储资源.利用排序链表存储中值滤波的原始数据,避免了其他中值滤波算法在排序时必需的数据移动或交换,使中值滤波算法中的排序计算量降低到O(N)级,提高了算法效率.实测对比表明,提出的中值滤波算法的存储器使用量至多是传统中值滤波算法的37%,运算速度至少是Matlab函数库medfiltl()给定算法的2倍.     

基于噪声点检测的中值滤波方法

提出了一种基于DS证据理论的滤波方法,用于去除两种类型的脉冲噪声,这种新的滤波方法由检测和滤波两部分组成.首先获得证据,并用窗中的信息定义集合函数;然后用决定规则来判定噪声是否存在.最后在滤波过程中,对检测到的噪声点用本文中的滤波方法进行处理,而好的象素点保持不变,这就避免了对非噪声象素点的破坏.从实验结果中可以看到,本文的方法对固定值和随机值的脉冲噪声都能有效抑制,并且可以保留图像细节.     

Geometric Features-Based Filtering for Suppression of Impulse Noise in Color Images

A geometric features-based filtering technique, named as the adaptive geometric features based filtering technique (AGFF), is presented for removal of impulse noise in corrupted color images. In contrast with the traditional noise detection techniques where only 1-D statistical information is used for noise detection and estimation, a novel noise detection method is proposed based on geometric characteristics and features (i.e., the 2-D information) of the corrupted pixel or the pixel region, leading to effective and efficient noise detection and estimation outcomes. A progressive restoration mechanism is devised using multipass nonlinear operations which adapt to the intensity and the types of the noise. Extensive experiments conducted using a wide range of test color images have shown that the AGFF is superior to a number of existing well-known benchmark techniques, in terms of standard image restoration performance criteria, including objective measurements, the visual image quality, and the computational complexity.      

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     

消除脉冲噪声的改进自适应滤波算法

针对灰度图像受脉冲噪声污染后的恢复处理问题,提出了一种改进的自适应中值滤波算法。该方法根据脉冲噪声的分布特点,采用极大值、极小值和领域均值判定准则进行噪声点的检测,然后用检测窗口内最小非噪声点集合的中值作为噪声点的滤波输出。实验结果表明,与其他几种算法相比,文中算法不仅在峰值信噪比(Peak Signal to Noise Ratio)和结构相似度(Structural Similarity,SSIM)上有较大优势,而且还具有较低的时间复杂度和更好的自适应性。也进一步说明该方法不仅能有效地检测并滤除噪声点,还能较好地保护图像的边缘细节。     

脉冲噪声下一种自适应ASR稳健滤波方法

在基于alpha稳定分布模型的脉冲噪声处理领域中,经典滤波方法多采用Cauchy分布和Meridian分布等alpha稳定分布特例,其脉冲抑制能力有限。对此,该文基于M估计理论和$ {\rm{AS}}\alpha {\rm{S}} $分布模型,构造稳健滤波代价函数簇,提出ASR稳健滤波方法,利用影响函数分析其稳健性,构建稳健滤波的统一理论基础,将Myriad滤波,Meridian滤波统一起来。给出线性度参数表达式,并采用阈值选择法实现自适应选择。此外,提出AS-FT滤波方法,以线性调频(LFM)信号在脉冲噪声下的参数估计为例,表明ASR滤波方法的稳健性。仿真实验表明,ASR稳健滤波方法,与中值滤波、Myriad滤波、分数低阶等传统的稳健滤波方法相比,具有良好的鲁棒性。     

脉冲噪声下一种自适应ASR稳健滤波方法

在基于alpha稳定分布模型的脉冲噪声处理领域中,经典滤波方法多采用Cauchy分布和Meridian分布等alpha稳定分布特例,其脉冲抑制能力有限.对此,该文基于M估计理论和ASαS分布模型,构造稳健滤波代价函数簇,提出ASR稳健滤波方法,利用影响函数分析其稳健性,构建稳健滤波的统一理论基础,将Myriad滤波,Meridian滤波统一起来.给出线性度参数表达式,并采用阈值选择法实现自适应选择.此外,提出AS-FT滤波方法,以线性调频(LFM)信号在脉冲噪声下的参数估计为例,表明ASR滤波方法的稳健性.仿真实验表明,ASR稳健滤波方法,与中值滤波、Myriad滤波、分数低阶等传统的稳健滤波方法相比,具有良好的鲁棒性.     

基于×字形窗口的自适应中值滤波算法

传统的中值滤波方法在去除脉冲噪声的同时会损失部分图像细节,且运行速度也不能很好地满足实时性要求。在此对Matlab工具箱中的中值滤波算法进行改进,提出一种基于×字形滤波窗口的自适应中值滤波算法。该方法具有根据3×3的×字形窗口中噪声点个数自适应调整滤波窗口大小及根据矩阵的对称性及基本的逻辑运算实现×字形窗口的特点。实验结果表明,与传统的方形窗口中值滤波算法相比,该方法在有效去除椒盐噪声和脉冲噪声的同时,较好地保持了图像细节,缩短了运行时间。     

一种新的干涉相位图局部自适应滤波方法

为了有效提高对InSAR干涉相位噪声的抑制性能并充分保持干涉相位图细节信息,该文提出一种基于局部地形相位补偿和各向异性高斯滤波函数(AGF)的自适应复相位滤波方法。该方法首先利用局部频率估计方法补偿地形相位,以便于消除局部地形相位对滤波窗口内干涉相位的不利影响。然后,构造了尺度和方向自适应的AGF,并对同分布样本进行局部加权的方向滤波。这里,AGF尺度随相干系数等级自适应变化：在低相干区域,采用的大尺度AGF能够充分地抑制相位噪声;在高相干区域,采用的小尺度AGF能更好地保持相位细节信息。AGF方向根据最大加权相干积累准则确定,以选取同分布的滤波样本估计中心像素相位值。实验结果表明,与多种滤波方法相比,该文方法在减少干涉相位图残点和保持条纹边缘等方面均具有更好的性能。     

Adaptive Detection of Signals in Impulsive Noise Environments

A detector structure and an adaptive algorithm are proposed for the reception of signals in noise backgrounds possessing broad-tailed probability distributions typical of impulsive noise. The adaptive detector combines the best features of linear matched filtering and hard-limiting receiver structures resulting in a small-signal SNR performance which is an improvement over either of these detectors alone. Furthermore, the adaptive detector is relatively easy to implement and is shown to provide efficient and robust performance for a wide range of underlying noise distributions.     

DPCM Coders with Adaptive Prediction for NTSC Composite TV Signals

New adaptive differential pulse code modulation (ADPCM) coders with adaptive prediction are proposed and compared with existing nonadaptive DPCM coders, for processing composite National Television System Commission (NTSC) television signals. Comparisons are based on quantative criteria as well as subjective evaluation of the processed still frames. The performance of the proposed predictors is shown to be independent of well-designed quantizers and better than existing predictors in such critical regions of the pictures as edges and contours.     

红外图像噪声先验中值滤波方法的设计与应用

红外图像中的脉冲噪声影响温度测量及分析,同时影响红外图像的可观性。传统中值滤波容易造成过度滤波,影响温度分布,丢失图像温度信息。针对传统方法的缺陷,借鉴噪声检测的中值滤波方法,将其应用于红外图像的脉冲噪声滤波。该方法在中值滤波之前进行一次脉冲噪声检测,确定受到噪声污染的像素点,并进行记录标识。然后进行对噪声污染像素的针对性滤波,实验证明,达到了既能有效滤除噪声,又完整保留温度信息的目的。