非约束维纳滤波综合鉴别函数算法研究

通过去掉最小平均相关能量匹配滤波器推导过程中对输出相关峰值的约束条件,定义相关判据,得出畸变不变相关识别综合鉴别函数形式为维纳滤波函数,不仅抗噪能力强,且把非约束匹配滤波器畸变容限大的优点引入其中.模拟结果表明,所设计匹配滤波器畸变容限大、抗噪能力强.     

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.     

Generalized Maximum Complex Correntropy Augmented Adaptive IIR Filtering

Augmented IIR filter adaptive algorithms have been considered in many studies, which are suitable for proper and improper complex-valued signals. However, lots of augmented IIR filter adaptive algorithms are developed under the mean square error (MSE) criterion. It is an ideal optimality criterion under Gaussian noises but fails to model the behavior of non-Gaussian noise found in practice. Complex correntropy has shown robustness under non-Gaussian noises in the design of adaptive filters as a similarity measure for the complex random variables. In this paper, we propose a new augmented IIR filter adaptive algorithm based on the generalized maximum complex correntropy criterion (GMCCC-AIIR), which employs the complex generalized Gaussian density function as the kernel function. Stability analysis provides the bound of learning rate. Simulation results verify its superiority.     

Correlation recognition for range image of laser radar

The target recognition of laser radar becomes hot research in recent years, because laser radar can produce high space resolution and collect rich target information, such as range image, intensity image and Doppler image. In the vertical detection of laser radar, the problem of in-plane target rotation invariance is firstly solved. In the paper, a new support vector machine (SVM) correlation filter is presented, which simultaneously has the attractive attributes of SVM and common correlation filter. Exploiting the idea of margin of separation maximization, the design criterion is produced. The filter is synthetic by the multiple training images which are generated by rotating one image. The real range images of laser radar are used to finish the correlation experiments. The results show that the filter is not sensitive to the noise, the correlation peak is changed slightly for the different testing images, and the precision of location is high.This design way can be used in other recognition fields.     

一种新的卫星钟差Kalman滤波噪声协方差估计方法

采用Kalman滤波方法进行钟差参数计算和预报时, 需确定Kalman滤波噪声协方差矩阵. 针对这一问题, 提出了一种新的卫星钟差Kalman滤波噪声协方差估计方法, 通过建立新息的相关函数序列与未知的噪声参数间的线性函数模型, 采用最小二乘法进行噪声参数估计. 采用精密钟差数据进行钟差参数估计和预报分析, 结果表明, 该方法具有较好的收敛性, 并与顾及随机噪声模型的开窗分类因子自适应抗差估计方法进行对比分析, 验证了新方法的正确性和有效性.     

一种改进的小波除噪方法用于含噪ICP-AES光谱的处理

提出了一种改进的小波除噪方法。它基于噪声具有频率较高和幅度较小的特点 ,先排除信号中频率较高的成分 ,再丢弃余下的系数较小的成分。对模拟的含噪电感耦合等离子体原子发射光谱 (ICP AES)的处理结果表明 ,该法能克服小波平滑和小波去噪的一些缺陷 ,可去除更多噪声 ,而信号强度不受影响。同时 ,基线变得平坦 ,有利于峰高的定量计算。用该法处理实测ICP AES光谱 ,效果满意。     

基于背景噪音谱分析的匹配滤波器设计研究

在空间匹配滤波器设计过程中,为抑制输入场景中背景噪音对输出相关平面上相关点的影响,通过比较匹配滤波函数和背景噪音的傅里叶谱,根据两者差值的量级对匹配滤波函数的振幅进行非线性调制,在匹配滤波过程中使设计的空间匹配滤波器对强噪音的傅里叶谱处透过率降低,而尽量保持输入图像傅里叶谱的高透过率,从而增加输出相关平面上的信噪比,实现相关点的正确探测。计算机模拟和实验结果表明：与纯相位匹配滤波器相比其抗噪能力得到较大改善。     

Effect of Correlated Dichotomous Noises on Stochastic Resonance in a Linear System

A linear system driven by correlated asymmetric dichotomous noises and periodic signal was investigated in the overdamped case. The exact expressions of output signal amplitude and signal-to-noise ratio (SNR) of the system were derived. By means of numerical calculations, we found that: (i) At some fixed multiplicative noise intensities, the output signal amplitude with frequency exhibits the structure of a weak peak, even no peak as the dichotomous noise is asymmetric; (ii) In the case of asymmetric dichotomous noise, the signal frequency can cause non-monotonous behavior of the output signal amplitude with respect to multiplicative noise intensity; (iii) The curve of SNR with frequency has a weak peak and a trough in the case of symmetric dichotomous noise, but no peak with asymmetric; (iv) Whether the multiplicative noise is symmetric or asymmetric, the noise can enhance response of the system; (v) The SNR increases with the correlation strength between the two noises decreasing. In addition, the plane of multiplicative noise intensity versus noise symmetric parameter was plotted.     

Shift- and scale-invariant pattern recognition using morphological phase-only correlation

We propose a non-linear correlation to realize scale-invariant recognition, called shift- and scale-invariant morphological phase-only correlation (SSIMPC), which is a combination of radial harmonic filter (RHF) and morphological phase-only correlation (MPC). We form SSIMPC using phase-only RHFs (PORHF) instead of common RHFs in every sub-correlations of morphological radial harmonic correlation (MRHC). Computer simulation results demonstrate that the performance of SSIMPC is better than that of MRHC in discrimination and robustness against non-Gaussian noise, such as salt-and-pepper noise and cluttered background, and above of all, SSIMOC realizes approximately full scale-invariance. In addition, we devise an optoelectronic scheme, which is identical to the setup for MPC, to implement SSIMPC.     

频率域数字散斑相关方法的研究

提出一种利用二维快速傅里叶变换（ＦＦＴ）经频率域匹配滤波实现数字相关运算以提取散斑图携带位移信息的频率域数字散斑相关方法。该方法因采取快速傅里叶变换、散斑限幅、滤波器优化等措施而减弱了空间域相关方法中不利因素对相关波峰的影响,提出了相关点定位的时效性和精确性。     

Modified computational integral imaging-based double image encryption using fractional Fourier transform

In this paper, we propose an image encryption technique to simultaneously encrypt double or multiple images into one encrypted image using computational integral imaging (CII) and fractional Fourier transform (FrFT). In the encryption, each of the input plane images are located at different positions along a pickup plane, and simultaneously recorded in the form of an elemental image array (EIA) through a lenslet array. The recorded EIA to be encrypted is multiplied by FrFT with two different fractional orders. In order to mitigate the drawbacks of occlusion noise in computational integral imaging reconstruction (CIIR), the plane images can be reconstructed using a modified CIIR technique. To further improve the solution of the reconstructed plane images, a block matching algorithm is also introduced. Numerical simulation results verify the feasibility and effectiveness of the proposed method.     

Wavelet-modified fringe-adjusted joint transform correlator

In this paper, we implement a wavelet-modified fringe-adjusted joint transform correlator (JTC) for real-time target recognition applications. In real-time situation the input scene is captured using a charge-coupled device (CCD) camera. The obtained joint power spectrum is multiplied by a pre-synthesized fringe-adjusted filter and the resultant function is processed with an appropriately scaled wavelet filter. Three performance measure parameters: correlation peak intensity, peak-to-sidelobe ratio, and signal-to-clutter ratio have been calculated for fringe-adjusted joint transform correlator (FJTC) and wavelet-modified fringe-adjusted joint transform correlator (WFJTC). The WFJTC has been found to yield better results in comparison to conventional FJTC. To suppress the undesired strong dc, the resultant function is differentiated. Differential processing wavelet-modified fringe-adjusted joint power spectrum removes the zero-order spectra and hence improves the detection efficiency. To focus the correlation terms in different planes in order to capture one of the desired autocorrelation peaks and discard the strong dc and another autocorrelation peak, chirp-encoding technique has also been applied. Targets with Gaussian and speckle noise have also been used to check the correlation outputs. Computer simulation and experimental results are presented.     

Shot-noise detection of ultrasound-tagged photons in ultrasound-modulated optical imaging

We propose a new detection method for ultrasound-modulated optical tomography that allows us to perform parallel speckle detection with optimum shot-noise sensitivity, using a CCD camera. Moreover, we show that making use of a spatial filter system allows us to fully filter out speckle decorrelation noise. This method is confirmed by a test experiment.     

Digital speckle pattern interferometric (DSPI) and thermo-graphic investigations on the thermal responds in human teeth

Human dentine is a composite material made up of constituents of varying thermal properties, which when subjected to changes in temperature experiences complex thermal effects. In this study, the response of functionally adapted dentine to temperature changes in physiological range is analyzed using a digital speckle pattern interferometer (DSPI) and thermography in conjunction with an advanced digital fringe processing technique. The advanced digital fringe processing is conducted using an asymmetric and central peak Gaussian filter, in order to remove noise and, subsequently, enhance the quality of the images. This investigation demonstrates the responds of functionally adapted dentine to temperature changes in its own plane and out of plane. Distinct pattern of out-of-plane and in-plane displacement was observed on the dentine by the DSPI analysis. The thermo-graphic analysis was used to rationalize the above nature of deformation in the dentine. These analyses showed that the inner, cervical dentine exhibited conspicuous deformation at the maximum temperature rise and equilibrated last during temperature drop.     

Combined digital filtering of harmonic content of phase-shift keyed signals in the problem of estimation of the time delay

We propose a two-step method for digital filtering of phase-shift keyed signals filtering in the problem of determination of the time delay during the multichannel propagation. The first step is realized as an information-optimal linear filter with complex coefficients, while the second step, as a quadratic filter based on the minimum-variance criterion. The e.ciency of the proposed method is demonstrated for short PSK signals with various carrier frequencies against the background of additive and multiplicative noise. The developed algorithm can easily be implemented in real time on the basis of a digital signal processor. __________ Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 50, No. 3, pp. 255–264, March 2007.     

Modified LACIF filtering in background disjoint noise

This work deals with pattern recognition methods based on correlations for images in the presence of noise. We propose a modification of the nonlinear Locally Adaptive Contrast Invariant Filter (LACIF) that yields correlation peaks that are invariant to linear intensity changes of the target but that has some limitations in the presence low variance nonoverlapping background noise. The modification of the filter implies a normalization by a global variance of several distributions. The estimation of the variance distributions is done locally by means of correlations. Experimental results as well as comparisons with the classical matched filter and the common LACIF are given.     

Relevant modes selection method based on Spearman correlation coefficient for laser signal denoising using empirical mode decomposition

Empirical mode decomposition (EMD) is a recently proposed nonlinear and nonstationary laser signal denoising method. A noisy signal is broken down using EMD into oscillatory components that are called intrinsic mode functions (IMFs). Thresholding-based denoising and correlation-based partial reconstruction of IMFs are the two main research directions for EMD-based denoising. Similar to other decomposition-based denoising approaches, EMD-based denoising methods require a reliable threshold to determine which IMFs are noise components and which IMFs are noise-free components. In this work, we propose a new approach in which each IMF is first denoised using EMD interval thresholding (EMD-IT), and then a robust thresholding process based on Spearman correlation coefficient is used for relevant modes selection. The proposed method tackles the problem using a thresholding-based denoising approach coupled with partial reconstruction of the relevant IMFs. Other traditional denoising methods, including correlation-based EMD partial reconstruction (EMD-Correlation), discrete Fourier transform and wavelet-based methods, are investigated to provide a comparison with the proposed technique. Simulation and test results demonstrate the superior performance of the proposed method when compared with the other methods.     

Acoustical inverse problems regularization: Direct definition of filter factors using Signal-to-Noise Ratio

Acoustic imaging aims at localization and characterization of sound sources using microphone arrays. In this paper a new regularization method for acoustic imaging by inverse approach is proposed. The method first relies on the singular value decomposition of the plant matrix and on the projection of the measured data on the corresponding singular vectors. In place of regularization using classical methods such as truncated singular value decomposition and Tikhonov regularization, the proposed method involves the direct definition of the filter factors on the basis of a thresholding operation, defined from the estimated measurement noise. The thresholding operation is achieved using modified filter functions. The originality of the approach is to propose the definition of a filter factor which provides more damping to the singular components dominated by noise than that given by the Tikhonov filter. This has the advantage of potentially simplifying the selection of the best regularization amount in inverse problems. Theoretical results show that this method is comparatively more accurate than Tikhonov regularization and truncated singular value decomposition.     

Composite wavelet based morphological correlation for continuous-scale-invariant pattern recognition

A composite nonlinear correlation is proposed to perform invariant recognition for the input image with continuous-scale distortions. The proposed correlation can be considered as a summation of many composite wavelet matched filters. Every matched filter consists of a linear combination of binary slices that are generated from threshold decomposition of the training images, and an adaptive wavelet filter. The adaptive wavelet is optimized to produce the sparse image features. Computer simulations are carried out to prove the scale-invariance and noise robustness of the new scheme.     

Reduction of Fringe Noise in Wavelength Modulation Spectroscopy Using a One-Dimensional Focal Plane Array

In wavelength modulation spectroscopy using diode lasers, detection limit of molecular absorption is often imposed by spurious fringe noises that arise from slight reflections among optical components. In an attempt to reduce this fringe effect, we propose and demonstrate the use of a one-dimensional focal plane array. With the help of a multiplexer, a single lock-in amplifier is employed to obtain multiple-channel signals from wavelength-modulated output of an array detector. It is found that the intensity change of the molecular absorption signal is nearly proportional to the transversal beam intensity distribution, whereas that of fringe noise is much less conspicuous. These features, as well as the phase difference among the channels, contribute to separate the signal and fringe noise components from the multiplexed spectra, leading to the overall improvement in the signal-to-noise ratio.