Study and design of exponential and Butterworth low-pass filters used for digital speckle interference fringe filtering

This paper studies the exponential and Butterworth low-pass filtering methods and proposes improved exponential and Butterworth low-pass filters. The improved low-pass filters proposed in the paper can be used effectively for filtering processing of digital speckle interference fringes obtained in digital speckle pattern interferometry. Both theoretical analysis and experimental results are presented in the paper.     

数字全息图再现像的像质改善

基于数字图像处理技术,提出了一套对数字全息图及其再现像进行处理的方法,改善了数字全息图再现像的像质.利用频谱匹配滤波的方法可以有效地滤除零级及孪生像干扰.同时,提出了通过均值滤波、中值滤波等方法降低激光散斑噪音的技术.理论和实验证明,综合而又合理地利用数字图像处理技术可以很大程度地改善数字全息图再现像的像质.     

Improved Quantum Image Median Filtering in the Spatial Domain

In some image processing algorithms, such as those for image feature extraction and segmentation, filtering is a significant pre-processing step to remove noises and improve image quality. An improved quantum image median filtering approach is proposed, and its corresponding quantum circuit is designed in this work. The main idea of the approach is that first the classical image is converted into a quantum version based on the novel enhanced quantum representation (NEQR) of digital images, and then a unique quantum module is designed to realize the median calculation of neighborhood pixels for each pixel point in the image. Finally, in order to improve the filtering effect, extremum detection is employed to distinguish noises from true signals. The experimental results show that a competitive filtering performance is obtained compared with previous methods. In addition, a network complexity analysis of the quantum circuit suggests that the proposed filtering approach can perform enormous speed-up over its corresponding classical counterparts.

     

电子散斑干涉条纹的计算机自动处理

电子散斑干涉条纹的噪声较强,一些常用的图像去噪、二值化、细化等算法对散斑干涉条纹的处理都存在一定的不足.针对散斑条纹的灰度值具有由两边向中间逐渐增强的特点,提出了一种新的计算机自动处理算法.该方法首先对干涉条纹进行巴特沃思滤波去噪、二值化,然后对其应用Hilditch细化计算机,实验结果表明此算法能较好地对一幅散斑干涉条纹图像进行细化.     

Phase retrieval in DSSI for relatively large deformation

Methods for phase retrieval in digital speckle shearing interferometry (DSSI) with relatively large deformation are proposed using a single wavelength illumination with windowed Fourier filtering (WFF) and two-wavelength simultaneous illumination with iterative sine-cosine average filtering (ISCAF). For relatively large deformation measurement, WFF technique has a higher noise suppression capability than ISCAF technique but requires careful selection of the processing parameters, while ISCAF is a simple filtering with less parameter setting. Both methods for phase retrieval are discussed. Experimental results show that both methods are capable of noise suppression in the phase retrieval for relatively large deformation.     

自由飞行昆虫运动变形测量中弱光条提取

通过分析昆虫自由飞行状态下结构光光条图像的特点,提出了一种用于提取昆虫运动变形测量中弱光条中心点的图像处理方法。该方法根据图像的灰度分布情况对图像进行分块,采用小波理论对图像消噪,利用模糊增强和小波同态滤波相结合的算法增强各图像的弱光条信号,再应用steger算法提取弱光条中心点的亚像素位置。给出几种算法实验结果的比较和分析,表明该方法成功实现了弱光条信号中心点的提取,并有效抑制了噪声和干扰。     

分数傅里叶变换啁啾滤波

针对常规傅里叶变换所不能解决的啁啾噪声滤除问题,利用Wigner分布函数分析分数傅里叶变换的空域和频域特性,提出在分数傅里叶变换域进行啁啾滤波的方法。并将该方法应用到图像处理中,对分数傅里叶变换滤除一维和二维图像的啁啾噪声进行了计算机仿真,获得了满意的效果,结果表明该方法在图像处理中的有效性。     

数字散斑条纹图的滤波方法

在现代数字散斑测量方法中，一般采用减模式来产生数字散斑条纹图，它是进一步图像处理的信息载体，同时不可避免地附带有大量的乘性噪声。为了保证测量精度，在进一步图像处理前必须对其进行降噪，选择合适的滤波方法显得尤为重要。在多年实际经验及阅读了大量文献的基础上，该文对国内外常用的数字散斑干涉条纹图滤波方法进行了分类阐述，选择了一些有代表性的方法予以实现，给出实验结果，并进行了对比分析。最后对数字散斑干涉条纹图滤波方法的发展方向给出了自己的看法。     

Complex noise suppression using a sparse representation and 3D filtering of images

A novel method for the filtering of images corrupted by complex noise composed of randomly distributed impulses and additive Gaussian noise has been substantiated for the first time. The method consists of three main stages: the detection and filtering of pixels corrupted by impulsive noise, the subsequent image processing to suppress the additive noise based on 3D filtering and a sparse representation of signals in a basis of wavelets, and the concluding image processing procedure to clean the final image of the errors emerged at the previous stages. A physical interpretation of the filtering method under complex noise conditions is given. A filtering block diagram has been developed in accordance with the novel approach. Simulations of the novel image filtering method have shown an advantage of the proposed filtering scheme in terms of generally recognized criteria, such as the structural similarity index measure and the peak signal-to-noise ratio, and when visually comparing the filtered images.     

成像型激光探测系统动态范围扩展技术研究

 针对成像型激光探测系统动态范围不足的问题,以现有广角远心鱼眼透镜和CMOS摄像器件为硬件基础,提出通过图像处理的方法扩展系统动态范围。系统采用帧相减技术滤除背景干扰和噪声,进而进行激光光斑的识别和定位。在此基础上,针对接收激光能量的不同,提出采用不同方法扩展动态范围。当激光能量较低时,激光信号可能淹没在噪声中无法准确判读和精确定位,通过滤波技术排除噪声,提高图像信噪比,从而提高系统探测灵敏度,即扩展探测下限。对于探测上限,即当强激光入射时,由于鱼眼光学系统内会产生反射干扰光,有可能在成像面形成不规则的干扰光斑,通过光斑匹配模式识别的方法排除杂光干扰,提高识别上限。实验结果表明,该方法使系统动态范围从为70 dB提高到89 dB,提高近30%,有效扩大了探测系统的作用范围。     

Image feature extraction by dynamic neural filtering and phase-only joint transform correlation

Neural network-based image processing algorithms present numerous advantages due to their supervised adjustable properties. Among various neural network architectures, dynamic neural networks, Hopfield and Cellular networks, have been found inherently suitable for filtering applications. Combining supervised and filtering features of dynamic neural networks, this paper presents dynamic neural filtering technique based on Hopfield neural network architecture. The filtering technique has also been implemented by using phase-only joint transform correlation (POJTC) for optical image processing applications. Filtering structure is basically similar to the Hopfield neural network structure except for the adjustable filter mask and 2D convolution operation instead of weight matrix operations. The dynamic neural filtering architecture has learnable properties by back-propagation learning algorithm. POJTC presents significant advantages to achieve the operation of summing the cross-correlation of bipolar data by phase-encoding bipolar data in parallel. The image feature extraction performance of the proposed optical system is reported for various image processing applications using a simulation program.     

Switching non-local vector median filter

This paper describes a novel image filtering method that removes random-valued impulse noise superimposed on a natural color image. In impulse noise removal, it is essential to employ a switching-type filtering method, as used in the well-known switching median filter, to preserve the detail of an original image with good quality. In color image filtering, it is generally preferable to deal with the red (R), green (G), and blue (B) components of each pixel of a color image as elements of a vectorized signal, as in the well-known vector median filter, rather than as component-wise signals to prevent a color shift after filtering. By taking these fundamentals into consideration, we propose a switching-type vector median filter with non-local processing that mainly consists of a noise detector and a noise removal filter. Concretely, we propose a noise detector that proactively detects noise-corrupted pixels by focusing attention on the isolation tendencies of pixels of interest not in an input image but in difference images between RGB components. Furthermore, as the noise removal filter, we propose an extended version of the non-local median filter, we proposed previously for grayscale image processing, named the non-local vector median filter, which is designed for color image processing. The proposed method realizes a superior balance between the preservation of detail and impulse noise removal by proactive noise detection and non-local switching vector median filtering, respectively. The effectiveness and validity of the proposed method are verified in a series of experiments using natural color images.     

Wavelet analysis of ellipticity,dispersion, and dissipation properties of Rayleigh waves

This paper is devoted to the digital processing of multicomponent seismograms using wavelet analysis. The goal of this processing is to identify Rayleigh surface elastic waves and determine their properties. A new method for calculating the ellipticity parameters of a wave in the form of a time-frequency spectrum is proposed, which offers wide possibilities for filtering seismic signals in order to suppress or extract the Rayleigh components. A model of dispersion and dissipation of elliptic waves written in terms of wavelet spectra of complex (two-component) signals is also proposed. The model is used to formulate a nonlinear minimization problem that allows for a high-accuracy calculation of the group and phase velocities and the attenuation factor for a propagating elliptic Rayleigh wave. All methods considered in the paper are illustrated with the use of test signals.     

基于EMD-DISPO的Mie散射激光雷达回波信号去噪方法研究

激光雷达回波信号是典型的非稳态、非平稳信号,用传统的滤波方法难以对其进行有效地处理.利用经验模式分解方法(EMD)将信号按照不同的特征时间尺度分解为不同的IMF分量,将含有噪声的高频IMF分量剔除,可达到去噪的目的.但如果简单地将高频分量直接剔除,有可能造成有效信号的损失.可提出将EMD方法与Savitzky-Gola...     

Research on Computer-Aided Diagnosis Method Based on Symptom Filtering and Weighted Network

In the process of disease identification, as the number of diseases increases, the collection of both diseases and symptoms becomes larger. However, existing computer-aided diagnosis systems do not completely solve the dimensional disaster caused by the increasing data set. To address the above problems, we propose methods of using symptom filtering and a weighted network with the goal of deeper processing of the collected symptom information. Symptom filtering is similar to a filter in signal transmission, which can filter the collected symptom information, further reduce the dimensional space of the system, and make the important symptoms more prominent. The weighted network, on the other hand, mines deeper disease information by modeling the channels of symptom information, amplifying important information, and suppressing unimportant information. Compared with existing hierarchical reinforcement learning models, the feature extraction methods proposed in this paper can help existing models improve their accuracy by more than 10%.     

基于多引导滤波的图像增强算法

图像增强技术可以有效地突出图像中的有用信息,已广泛应用于多个领域.现有的图像增强算法往往无法应对自然图像中复杂的梯度分布,难以准确保持图像中前景与背景的边缘信息.为了改善输出图像的边界过平滑问题,本文提出了一个基于多引导滤波的图像增强算法.首先,设计了一个以滤波核为变量的通用图像优化模型,现有的联合滤波器可视为该模型的解;然后,依据集成学习的思想,将联合滤波器中的单幅引导图像扩展到多幅,以更好地利用引导图中的结构信息进而获得更好的输出结果,并给出了一个多幅引导图的来源途径;最后,对多幅输出图像进行平滑,在图像优化模型中加入正则化项,以确保由多引导滤波得到的不同滤波输出保持一致.实验结果表明,本文算法在抑制图像噪声的同时,可以更好地保留物体的边界信息,从而使图像的信噪比进一步提升.     

改进Canny算法的红外人脸图像边缘轮廓提取

红外人脸图像的边缘轮廓特征对于红外人脸检测、识别等相关应用具有重要价值。针对红外人脸图像边缘轮廓提取时存在伪边缘的问题,提出了一种改进Canny算法的红外人脸图像边缘轮廓提取方法。首先通过对引导滤波算法引入“动态阈值约束因子”替换原始算法中的高斯滤波,解决了原始算法滤波处理不均匀和造成红外人脸图像弱边缘特征丢失的弊端;接着对原始算法的非极大值抑制进行了改进,在原始计算梯度方向的基础上又增加了4个梯度方向,使得非极大值抑制的插值较原始算法更加精细;最后改进OTSU(大津)算法,构造灰度-梯度映射函数确定最佳阈值,解决了原始算法人为经验确定阈值的局限性。实验结果表明:提出的改进Canny算法的红外人脸轮廓提取方法滤波后的图像,相较于原始Canny算法滤波处理,信噪比性能提升了34.40%,结构相似度性能提升了21.66%;最终的红外人脸边缘轮廓提取实验的优质系数值高于对比实验的其他方法,证明改进后的算法对于红外人脸图像边缘轮廓提取具有优越性。     

基于小波变换的卡尔曼滤波法在ICP-AES中的应用

在ICP－AES中，卡尔曼滤波是一种有效的光谱干扰校正方法，它在强背景、谱线重叠严重的情况下，仍可得到很好的分析结果；并且有比传统分析线法在纯组分试样条件下更低的检出限。然而，噪声的存在影响了卡尔曼滤波的准确度。小波变换因其多分辨分析的特性，近年来被用于分析信号的去噪，而且该方法简单、快速，是一种很有效的去噪方法。本文首先用仿真数据研究了噪声对卡尔曼滤波法的影响；其次，将小波变换引入卡尔曼滤波法，提出了基于小波变换的卡尔曼滤波法，仿真实验结果表明，该方法能有效提高卡尔曼滤波法的分析准确度。     

THz激光主动图像预处理方法研究

鉴于THz激光主动成像以其较低的光子能量和较高的穿透能力在危险品检测、医疗和食品检验等领域有着广泛的应用前景,将对比度拉伸变换、中值滤波和均值滤波常规图像预处理方法引入到THz激光主动图像处理中,对五元人民币纸币的水印THz面阵图像进行了预处理。处理结果表明,对原始图像进行对比度拉伸变换可以较大地提高图像对比度,在此基础上进行的中值滤波和均值滤波可进一步提高图像的辨识能力,中值滤波可以保护目标边缘细节并使图像平滑。在对比中发现,当窗口大小为9×9像元时滤波后的视觉效果最佳。     

Wave number-frequency spectrum of turbulent pressure fluctuations: Methods of measurement and results

The methods proposed earlier for measuring the wave number-frequency spectrum of wall pressure fluctuations beneath a turbulent boundary layer are considered: the spatial filtering of the pressure field components by special-purpose transducers (wave filters) and the digital processing of signals obtained from an array of transducers. It is shown that, for the wave filters, transducers with a rectangular shape of sensitive surface rather than those with a circular one are necessary. Results of measuring the wave number-frequency spectrum of turbulent pressure fluctuations in a low-noise wind tunnel are presented. The measurements are performed with the use of four wave filters consisting of rectangular transducers with a constant sensitivity distribution over their surfaces. The mathematical model of the wave number-frequency spectrum proposed earlier by the authors is compared with the measurement data reported by Abraham and Keith. The model is used for processing the results of measurements in the wind tunnel. The measured spectra are compared with the data obtained by Martin and Leehey.