Estimation of the surface velocity of debris flow with computer-based spatial filtering

A computer-based spatial-filtering velocimeter to measure the surface velocity of natural debris flow is described. This is a simple and interesting technique implemented with a spatial filter constructed as a software program that processes the video image of debris flow instead of a hardware implementation. The surface velocity of the debris flow at the Mt. Yakedake Volcano, Japan, was estimated by this computer-based spatial-filtering method, and the results were compared with those obtained by a hardware-based spatial-filtering method. Computer-based spatial filtering has the important advantage of a capability for tuning the spatial-filter parameters to the target flow.     

经验模态分解和空间滤波在两相流速度测量中的应用

在利用空间滤波和电容传感器测量两相流速度时,需要准确测量电容传感器输出信号的带宽.针对此问题提出一种利用经验模态分解算法来测量传感器带宽的方法.文章首先介绍电容传感器的空间滤波效应和经验模态分解的基本原理,并给出固体速度和电容传感器输出信号带宽之间的关系.然后将经验模态分解和平滑滤波器结合对测量信号进行平滑处理,测量处...     

一种结合时间轴滤波的视频消噪新方法

为了提高含噪视频图像的质量,提出了一种二维小波域自适应滤波与时域时间轴滤波相结合的视频图像消噪新方法。首先,对视频序列的各帧在二维小波域中进行自适应滤波,之后在时域中进行时间轴滤波。对于二维小波域滤波算法,提出了一种高效的自适应阈值选取方案;时间轴滤波器则是结合了运动检测和递归平均。实验结果表明,其消噪效果要优于单纯的二维小波域滤波方法。     

Clutter filters adapted to tissue motion in ultrasound color flow imaging

The quality of ultrasound color flow images is highly dependent on sufficient attenuation of the clutter signals originating from stationary and slowly moving tissue. Without sufficient clutter rejection, the detection of low velocity blood flow will be poor, and the velocity estimates will have a large bias. In some situations, e.g., when imaging the coronary arteries or when the operator moves the probe in search for small vessels, there is considerable movement of tissue. It has been suggested that clutter rejection can be improved by mixing down the signal with an estimate of the mean frequency prior to high pass filtering. In this paper, we compare this algorithm with several other adaptive clutter filtering algorithms using both experimental data and simulations. We found that realistic accelerations of the tissue have a large effect on the clutter rejection. The best results were obtained by mixing down the signal with non-constant phase increments estimated from the signal. This adapted the filter to a possibly accelerated tissue motion and produced a significant improvement in clutter rejection     

Design of adaptive digital filters for phase extraction in complex fringe patterns obtained using the Ronchi test

A powerful technique is presented for processing complex fringe patterns with high noise levels and arbitrary distributions of spatial frequencies, which can successfully extract the phase information. Artifacts that arise from phase extraction in local filtering approaches are avoided by using a simple design and implementation strategy for the adaptive filter, based on the theory of digital filter design used in electronics, and applied to pixel rows (or columns) in the fringe-pattern. The filter designed in this manner is then applied to phase extraction in an experimental fringe pattern measured in a digital Ronchi test setup using a Carré phase-shifting procedure. The filtering strategy has a very low computational cost and allows phase extraction in noisy ronchigrams regardless their spatial frequency distribution, provided the fringes are still visible.     

Comparison of BaTiO3 optical novelty filter and photothermal lensing configurations in photothermal experiments.

Photorefractive BaTIO3 is used as an optical novelty filter to highlight the high spatial frequency components of the photothermal signal. A real-time phase grating recorded in BaTIO3 acts as a matched rejection spatial filter for the probe laser. This reduces the stationary background from the optical signals thereby increasing signal contrast ratios. Rejection of the monotonous stationary signal provides a powerful means of improving the photothermal signal. This paper describes the construction of this novel apparatus and the experiments performed in order to compare its performance with photothermal lensing results. A theory that explains photothermal signal filtering with BaTIO3 as an adaptive spatial frequency filter is presented. Results comparing the optical signals obtained in a photothermal lensing experiments and those obtained in the BaTIO3 optical novelty filter experiments are presented. The optical novelty filter signals demonstrate a remarkable improvement in the signal contrasts for moderate photothermal-induced phase shifts.     

Image Denoising with Adaptive Weighted Graph Filtering

Graph filtering, which is founded on the theory of graph signal processing, is proved as a useful tool for image denoising. Most graph filtering methods focus on learning an ideal lowpass filter to remove noise, where clean images are restored from noisy ones by retaining the image components in low graph frequency bands. However, this lowpass filter has limited ability to separate the low-frequency noise from clean images such that it makes the denoising procedure less effective. To address this issue, we propose an adaptive weighted graph filtering (AWGF) method to replace the design of traditional ideal lowpass filter. In detail, we reassess the existing low-rank denoising method with adaptive regularizer learning (ARLLR) from the view of graph filtering. A shrinkage approach subsequently is presented on the graph frequency domain, where the components of noisy image are adaptively decreased in each band by calculating their component significances. As a result, it makes the proposed graph filtering more explainable and suitable for denoising. Meanwhile, we demonstrate a graph filter under the constraint of subspace representation is employed in the ARLLR method. Therefore, ARLLR can be treated as a special form of graph filtering. It not only enriches the theory of graph filtering, but also builds a bridge from the low-rank methods to the graph filtering methods. In the experiments, we perform the AWGF method with a graph filter generated by the classical graph Laplacian matrix. The results show our method can achieve a comparable denoising performance with several state-of-the-art denoising methods.     

Optimal Estimation of the Acceleration of a Car Under Performance Tests

In this paper, a recursive least-squares lattice (RLSL) adaptive filter was used to carry out the optimal estimation of the relevant signal coming from an accelerometer placed in car under performance tests. Here, the signal of interest is buried in a broadband noise background where we have little knowledge of the noise characteristics. In addition, due to the fact that the noise and the relevant information sometimes share the same or a very similar frequency spectrum, it is very difficult to cancel the noise that corrupts the relevant information without causing that information to deteriorate. The results of the experiment are satisfactory and, in order to compare classical filtering with optimal adaptive filtering, the signal coming from the accelerometer was also filtered by using a third-order lowpass digital Butterworth filter. The results of comparing the aforementioned filters show that the optimal adaptive filter is superior to the classical filter. Here, a significant improvement of 22.4 dB in the signal-to-noise ratio (SNR) at the RLSL adaptive filter output was achieved. However, the improvement in the SNR at the Butterworth filter output was 6.1 dB, which shows very clear that the optimal adaptive filter performs much better than the classical one     

Quantitative assessment of flow velocity-estimation algorithms for optical Doppler tomography imaging

We present a quantitative comparison of three categories of velocity estimation algorithms, including centroid techniques (the adaptive centroid technique and the weighted centroid technique), the sliding-window filtering technique, and correlation techniques (autocorrelation and cross correlation). We introduce, among these five algorithms, two new algorithms: weighted centroid and sliding-window filtering. Simulations and in vivo blood flow data are used to assess the velocity estimation accuracies of these algorithms. These comparisons demonstrate that the sliding-window filtering technique is superior to the other techniques in terms of velocity estimation accuracy and robustness to noise.     

卷积伏安法实验数据的自适应卡尔曼滤波 Ⅰ.数据的平滑

本文研究了自适应卡尔曼滤波技术在新极谱法中的应用。通过极谱法拟合数据试验结果表明,1∶N自适应卡尔曼滤波器用于消除新极谱法实验数据中噪声的干扰,效果极好,其滤波结果具有良好的线性关系。应用于Cd(Ⅱ)的半微分电分析实测数据的处理,取得令人满意的结果。     

一种自适应的图像双边滤波方法

提出一种利用双边滤波的图像平滑滤波方法,即在滤除图像中高频噪声的同时,按照图像亮度变化保持图像中处于高频部分的边缘信息的自适应滤波过程。该滤波方法将传统的Gauss滤波器的权系数优化成Gauss函数和图像的亮度信息乘积的形式,优化后的权系数再与图像作卷积运算。这样,滤波时就可以考虑到图像的亮度信息,在滤除图像噪声的同时尽量保持了图像的边缘。由于双边滤波的方法可以使滤波器的权系数随着图像的亮度变化而改变,所以在滤波过程中能达到自适应滤波的目的。     

Spectral Doppler estimation utilizing 2-D spatial information and adaptive signal processing

The trade-off between temporal and spectral resolution in conventional pulsed wave (PW) Doppler may limit duplex/triplex quality and the depiction of rapid flow events. It is therefore desirable to reduce the required observation window (OW) of the Doppler signal while preserving the frequency resolution. This work investigates how the required observation time can be reduced by adaptive spectral estimation utilizing 2-D spatial information obtained by parallel receive beamforming. Four adaptive estimation techniques were investigated, the power spectral Capon (PSC) method, the amplitude and phase estimation (APES) technique, multiple signal classification (MUSIC), and a projection-based version of the Capon technique. By averaging radially and laterally, the required covariance matrix could successfully be estimated without temporal averaging. Useful PW spectra of high resolution and contrast could be generated from ensembles corresponding to those used in color flow imaging (CFI; OW = 10). For a given OW, the frequency resolution could be increased compared with the Welch approach, in cases in which the transit time was higher or comparable to the observation time. In such cases, using short or long pulses with unfocused or focused transmit, an increase in temporal resolution of up to 4 to 6 times could be obtained in in vivo examples. It was further shown that by using adaptive signal processing, velocity spectra may be generated without high-pass filtering the Doppler signal. With the proposed approach, spectra retrospectively calculated from CFI may become useful for unfocused as well as focused imaging. This application may provide new clinical information by inspection of velocity spectra simultaneously from several spatial locations.     

基于自适应陷波的涡街流量计信号处理系统

本介绍了以数字信号处理器为核心的实时处理系统,采用自适应陷波方法计算涡街流量计信号的频率。自适应陷波器只需估计一个参数。采用了ＤＳＰ,使得信号处理实时和系统小型化。实测结果说明,自适应陷波方法和实时处理系统是有效的。     

Optimal velocity estimation in ultrasound color flow imaging in presence of clutter

In color flow imaging (CFI), the rejection of tissue clutter signal is treated separately from blood velocity estimation by high-pass filtering the received Doppler signal. The complete suppression of clutter is then difficult to achieve without affecting the subsequent velocity estimates. In this work, a different approach to velocity estimation is investigated, based on a statistical model of the signal from both clutter and blood. An analytic expression for the Cramer-Rao lower bound (CRLB) is developed, and used to determine the existence of an efficient maximum likelihood estimator (MLE) of blood velocity in CFI when assuming full knowledge of the clutter statistics. We further simulate and compare the performance of the MLE to that of the autocorrelation method (ACM) using finite-impulse response (FIR) and polynomial regression clutter filters. Two signal scenarios are simulated, representing a central and peripheral vessel. Simulations showed that, by including 3-9 (independent) spatial points, the MLE variance approached the CRLB in both scenarios. The ACM was approximately unbiased only for the central scenario in the clutter filter pass band, then with a variance of up to four times the CRLB. The ACM suffered from a severe bias in the filter transition region, and a significant performance gain was achieved here using the MLE. For practical use, the clutter properties must be estimated. We finally replaced the known clutter statistics with an estimate obtained from low-rank approximations of the received sample correlation matrix. Used in the model-based framework, this method came close to the performance of the MLE, and it may be an important step toward a practical model-based estimator, including tissue clutter with optimal performance.     

Quantitative analysis of debris from SiC-fiber-reinforced aluminum-alloy targets impacted by spherical projectiles

Silicon-carbide-continuous-fiber-reinforced aluminum matrix composite targets were impacted with duralumin projectiles at velocities from 2.9 km/s to 4.3 km/s. The debris from the composite targets was monitored by flash, soft x-ray radiography. The spatial distribution of the leading half of the debris were quantified in terms of mass, velocity, and kinetic energy and compared with that of debris from monolithic aluminum-alloy targets. A material effect on the debris production was found through the experiment so that fragments from the composite targets were smaller in mass and size, but more in number than those from the monolithic bumper. An increase of the impact velocity brought the enhancement of fragmentation in the leading edge part of the debris produced from both the composite and the monolithic targets in comparison with lower velocity impacts. The 4.3 km/s impact for the composite gave the spatial densities of debris mass and kinetic energy biased toward the periphery of the debris cloud, while other lower velocity impacts gave the different densities biased toward a gun axis. Such peripheral distribution of debris was found at an impact velocity of 3.5 km/s for the monolithic target. In the present velocity range, the composite debris always exhibited its larger peripheral distribution than the monolithic one did.     

插入式静电传感器特性研究

插入式静电传感器在测量气-固两相流参数和保证其传送安全方面有较好的应用。通过建立电极数学模型,讨论了插入式静电传感器电极的插入深度、空间滤波特性和空间灵敏度特性,得到固体颗粒位置对电极上感应电荷的影响情况、感应电极灵敏度分布规律和插入深度L与电极测量信号幅值之间关系。对于连续流动的固相颗粒,当插入式电极插入深度L为管道直径的1/2时为最佳尺寸,此时电极具有低通滤波特性。在利用电极数学模型对电极空间滤波特性理论推导的过程中获得了固相颗粒速度与测量信号截止频率的表达式。实测结果证实了电极的空间滤波特性和空间灵敏度特性。     

一种强噪声背景下的微弱信号检测的新方法

基于自适应滤波算法对小波滤波器的构造方法进行了研究,重点在于解决对强噪声环境下微弱信号提取所需要的小波变换的子带自适应滤波器的构造,把小波变换技术和自适应滤波技术应用于微弱信号的检测。提出基于自适应小波变换的心电信号的检测,利用小波变换的子带编码理论,通过在多个子带权值的自适应匹配,回复后拟合微弱信号。仿真结果表明,该方法可进一步改善信号的检测能力,在检测微弱信号的特征和改善信噪比方面是一种十分有效的方法。     

噪声概率快速估计的自适应椒盐噪声消除算法

提出一种可识别噪声概率自动调节滤波窗口的自适应椒盐噪声消除算法。对非理想椒盐噪声污染图像随机区域进行变窗口中值滤波,将结果与滤波前比对获得噪声点数,滤波区域即按此点数排序。然后取每种滤波窗口下的中间三组数据,该数据平均加权获取图像噪声概率初估计,对初估计平均加权即得图像噪声概率。滤波前首先采用阈值法排除明显噪声点,剩余像素中再以离窗口中心像素距离平方的倒数为权值估计中心像素。最后由噪声概率按照T-S模糊规则对不同模型的输出估计值进行融合。实验证明,与传统中值滤波等算法相比,该算法具有噪声自动估计和自适应窗口调节能力,滤波后标准均方差可减少20%以上,速度可提高一倍多。     

Real-time adaptive clutter rejection filtering in color flow imaging using power method iterations

We propose a new algorithm for real-time, adaptive-clutter-rejection filtering in ultrasound color flow imaging (CFI) and related techniques. The algorithm is based on regression filtering using eigenvectors of the signal correlation matrix as a basis for representing clutter, a method that previously has been considered too computationally demanding for real-time processing in general CFI applications. The data acquisition and processing scheme introduced allows for a more localized sampling of the clutter statistics and, therefore, an improved clutter attenuation for lower filter orders. By using the iterative power method technique, the dominant eigenvalues and corresponding eigenvectors of the correlation matrix can be estimated efficiently, rendering real-time operation feasible on desktop computers. A new adaptive filter order algorithm is proposed that successfully estimates the proper dimension of the clutter basis, previously one of the major drawbacks of this clutter-rejection technique. The filter algorithm performance and computational demands has been compared to that of conventional clutter filters. Examples have been included which confirms that, by adapting the clutter-rejection filter to estimates of the clutter-signal statistics, improved attenuation of the clutter signal can be achieved in normal as well as more excessive cases of tissue movement and acceleration.     

Adaptive-neighborhood speckle removal in multitemporal synthetic aperture radar images

We present a new method for multitemporal synthetic aperture radar image filtering using three-dimensional (3D) adaptive neighborhoods. The method takes both spatial and temporal information into account to derive the speckle-free value of a pixel. For each pixel individually, a 3D adaptive neighborhood is determined that contains only pixels belonging to the same distribution as the current pixel. Then statistics computed inside the established neighborhood are used to derive the filter output. It is shown that the method provides good results by drastically reducing speckle over homogeneous areas while retaining edges and thin structures. The performances of the proposed method are compared in terms of subjective and objective measures with those given by several classical speckle-filtering methods.