Blood velocity estimation using ultrasound and spectral iterative adaptive approaches

This paper proposes two novel iterative data-adaptive spectral estimation techniques for blood velocity estimation using medical ultrasound scanners. The techniques make no assumption on the sampling pattern of the emissions or the depth samples, allowing for duplex mode transmissions where B-mode images are interleaved with the Doppler emissions. Furthermore, the techniques are shown, using both simplified and more realistic Field II simulations as well as in vivo data, to outperform current state-of-the-art techniques, allowing for accurate estimation of the blood velocity spectrum using only 30% of the transmissions, thereby allowing for the examination of two separate vessel regions while retaining an adequate updating rate of the B-mode images. In addition, the proposed methods also allow for more flexible transmission patterns, as well as exhibit fewer spectral artifacts as compared to earlier techniques.     

Spatio-temporal nonrigid registration for ultrasound cardiac motion estimation

We propose a new spatio-temporal elastic registration algorithm for motion reconstruction from a series of images. The specific application is to estimate displacement fields from two-dimensional ultrasound sequences of the heart. The basic idea is to find a spatio-temporal deformation field that effectively compensates for the motion by minimizing a difference with respect to a reference frame. The key feature of our method is the use of a semi-local spatio-temporal parametric model for the deformation using splines, and the reformulation of the registration task as a global optimization problem. The scale of the spline model controls the smoothness of the displacement field. Our algorithm uses a multiresolution optimization strategy to obtain a higher speed and robustness. We evaluated the accuracy of our algorithm using a synthetic sequence generated with an ultrasound simulation package, together with a realistic cardiac motion model. We compared our new global multiframe approach with a previous method based on pairwise registration of consecutive frames to demonstrate the benefits of introducing temporal consistency. Finally, we applied the algorithm to the regional analysis of the left ventricle. Displacement and strain parameters were evaluated showing significant differences between the normal and pathological segments, thereby illustrating the clinical applicability of our method.     

A refined motion estimation strategy for adaptive interpolation filter

Adaptively selecting the filter coefficients for interpolating fractional pixels (sub-pel) can significantly improve the quality of reference pictures. However, the complexity of implementation is greatly increased by performing motion estimation (ME) and mode decision (MD) for multiple passes. This paper briefly introduces the adaptive interpolation filter (AIF) technique and proposes a refined ME strategy for realizing the AIF process with low complexity. By using this method, the 2-pass encoding procedure can be avoided while the coding efficiency of the AIF is maintained. The proposed method is implemented and verified on the AVS video software platform.     

一种适用于AVS-M的自适应快速运动估计算法

为了减小移动视频编码标准(AVS-M)中运动估计模块的复杂度,提出了一种快速、有效的块匹配运动估计算法.该算法充分利用了视频图像中运动矢量场的中心偏置特性和时空相关性,根据运动类型自适应的选择搜索起点和搜索策略,结合改进的搜索模板和高效搜索中止准则,有效地降低了运动估计的运算量.实验结果表明,该算法在保证搜索精度的同时,大大减少了搜索点数.     

Ultrasound speckle reduction using adaptive wavelet thresholding

Ultrasound is the most widely used biomedical imaging modality for the purpose of diagnosis. It often comes with speckle that results in reduced quality of images by hiding fine details like edges and boundaries, as well as texture information. In this present study, a novel wavelet thresholding technique for despeckling of ultrasound images is proposed. For analysing performance of the method, it is first tested on synthetic (ground truth) images. Speckle noise with distinct noise levels (0.01–0.04) has been added to the synthetic images in order to examine its efficiency at different noise levels. The proposed technique is applied to various orthogonal and biorthogonal wavelet filters. It has been observed that Daubechies 1 gives the best results out of all wavelet filters. The proposed method is further applied on ultrasound images. Performance of the proposed technique has been validated by comparing it with some state-of-the-art techniques. The results have also been validated visually by the expert. Results reveal that the proposed technique outperforms other state-of-the-art techniques in terms of edge preservation and similarities in structures. Thus, the technique is effective in reducing speckle noise in addition to preserving texture information that can be used for further processing.

     

一种新的自适应二值运动估计算法

利用增强位平面的二值特性和运动矢量场自适应思想,提出了一种新的自适应二值运动估计算法.算法在图像的位平面中完成运动矢量的搜索;匹配时对静止块进行判定直接中止搜索,同时采用了起始点预测和运动类型判定,自适应使用LDSP和SDSP模板进行搜索.实验结果表明:该算法的搜索速度优于绝大多数现有的运动估计算法,且预测精度接近于FS算法.     

Contourlet域超声图像自适应降斑算法研究

结合Contourlet系数的结构特点和超声图像相干斑乘性噪声模型,提出了一种新的基于Contourlet变换的斑纹噪声抑制算法.该算法通过计算方差一致性测度(VHM),用局部自适应窗口估计阈值萎缩因子,实现超声图像的降斑处理.实验结果表明,该算法在有效抑制斑纹噪声的同时,更有利于保持图像的边界信息,尤其适用于强噪声背景的超声图像.     

Simultaneous motion estimation and filtering of image sequences

We present an algorithm to simultaneously estimate multiple-frame motions and filter image sequences. The relative motion d(k)(x) between the reference frame s(x) and the kth frame s(x-d(k)(x)) in the presence of additive white Gaussian noise (AWGN) is estimated using the maximum-likelihood (ML) principle. The reference frame is also filtered in the linear minimum mean square error (LMMSE) sense during the process of motion estimation. Simulation experiments are performed using the affine motion model to illustrate the performance of this method.     

自适应阈值的快速运动估计算法

分析了视频序列运动场的基本特征,利用运动和匹配误差两种相关性,提出自适应阈值的快速运动估计算法(AT-FME),随编码对象的内容和运动情况自适应地调整阈值和搜索模式.实验结果表明,在匹配质量和码率相同情况下,AT-FME可比UMHexagonS节省62%的运算量,是提高视频压缩编码效率的有效方法.     

Sliding-mode motion controller with adaptive fuzzy disturbance estimation

This paper proposes a motion control scheme which belongs to the class of the control schemes known as sliding-mode control with disturbance estimation. A novel adaptive fuzzy disturbance estimator works as an estimator of a major part of robot dynamics. The adaptation algorithm is derived by using the Lyapunov stability theory and provides global asymptotic stability of the state errors, resulting in the sliding-mode regime. The structure of the disturbance estimator is optimized by the introduction of three fuzzy logic subsystems, based on the physical properties of the robot mechanism. This also significantly lowers the computational burden and enables real-time implementation. Performance of the proposed controller scheme, as well as some practical design aspects, are demonstrated by the control of a direct-drive robot.     

基于H.264的内容自适应分数像素运动估计算法

分数像素精确运动估计的改进是整个运动估计模块优化的关键,本文提出了基于H.264的内容自适应分数像素运动估计算法。首先,提出基于平坦区域宏块预测的无效分数像素运动矢量(MV)搜索省略算法(SMBP);然后,改进H.264采用的基于中心的分数像素搜索算法(CBFPS),提出基于预测矢量的增强型菱形模板(EDSP)搜索算法。实验结果表明,内容自适应分数像素运动估计算法比分数像素全搜索算法(FFPS)在峰值信噪比(PSNR)有微小降低(0.095～0.209 dB)的情况下,平均减少了75.6%的分数像素搜索点,整个运动估计模块平均节省了38.5%的计算量。     

Parameter estimation using pseudorandom binary sequences

The instrumental-variable technique for parameter estimation is applied when the input is a pseudorandom binary sequence (p.r.b.s.). The instrumental variables proposed are time-weighted elements of a p.r.b.s., and this is shown to be equivalent to obtaining the mean value of several estimates obtained from noisy measurements. The estimates of the parameters are asymptotically unbiased.     

Channel estimation using aperiodic binary sequences

Estimating a channel impulse response using a known aperiodic sequence is considered. The problem can be reduced to minimizing the trace of the inverse of a Toeplitz matrix. An efficient algorithm for computing this trace is developed and optimal binary sequences up to length 32 are found and tabulated. The use of complementary sequences in this context is also investigated. It is shown that the eigenvalues of the autocorrelation matrices of a pair of complementary sequences sum to a known constant     

Image motion estimation algorithms using cumulants

A class of algorithms is presented that estimates the displacement vector from two successive image frames consisting of signal plus noise. In the model, the signals are assumed to be either non-Gaussian or (quasistationary) deterministic; and, via a consistency result for cumulant estimators, the authors unify the stochastic and deterministic signal viewpoints. The noise sources are assumed to be Gaussian (perhaps spatially and temporally correlated) and of unknown covariance. Viewing image motion estimation as a 2D time delay estimation problem, the displacement vector of a moving object is estimated by solving linear equations involving third-order auto-cumulants and cross-cumulants. Additionally, a block-matching algorithm is developed that follows from a cumulant-error optimality criterion. Finally, the displacement vector for each pel is estimated using a recursive algorithm that minimizes a mean 2D fourth-order cumulant criterion. Simulation results are presented and discussed.     

Optimal sequences for channel estimation using discrete Fouriertransform techniques

This paper addresses the problem of selecting the optimum training sequence for channel estimation in communication systems over time-dispersive channels. By processing in the frequency domain, a new explicit form of search criterion is found, the gain loss factor (GLF), which minimizes the variance of the estimation error and is easy to compute. Theoretical upper and lower bounds on the GLF are derived. An efficient directed search strategy and optimal sequences up to length 42 are given. These sequences are optimal only for frequency domain estimation, not for time domain estimation     

Sub-pixel motion estimation using kernel methods

Modern video codecs such as MPEG2, MPEG4-ASP and H.264 depend on sub-pixel motion estimation to optimise rate-distortion efficiency. Sub-pixel motion estimation is implemented within these standards using interpolated values at 1/2 or 1/4 pixel accuracy. By using these interpolated values, the residual energy for each predicted macroblock is reduced. However this leads to a significant increase in complexity at the encoder, especially for H.264, where the cost of an exhaustive set of macroblock segmentations needs to be estimated for optimal mode selection. This paper presents a novel scheme for sub-pixel motion estimation based on the whole-pixel SAD distribution. Both half-pixel and quarter-pixel searches are guided by a model-free estimation of the SAD surface using a two dimensional kernel method. While giving an equivalent rate distortion performance, this approach approximately halves the number of quarter-pixel search positions giving an overall speed up of approximately 10% compared to the EPZS quarter-pixel method (the state of the art H.264 optimised sub-pixel motion estimator).     

Closed-form solution for circle pose estimation using binocular stereo vision

A simple method for pose estimation of a circle, with known circle radius, on the basis of binocular stereo vision is presented. The method is based on the projective equation of a circle, into which the stereo vision constraints are incorporated. The estimated pose parameters are compared with the ground truth and excellent performance is reported.