Motion estimation and compensation in the redundant-wavelet domain using triangle meshes

In this paper, a technique is presented that incorporates an irregular triangle mesh into wavelet-domain motion estimation and compensation using a shift-invariant redundant-wavelet transform. The main contribution of this work resides in a demonstration that triangle-mesh motion estimation and compensation can be deployed more effectively in the redundant-wavelet domain thanks to a simple correlation operator that is robust to the prediction residual, a noise-like signal that hinders spatial-domain gradient-based efforts to locate image edges which persist from frame to frame. In the proposed technique, motion compensation takes place through an affine transform mapping triangles from one frame to the next, while the motion-compensated residual is downsampled to a non-redundant form which is then coded using any wavelet-based still-image coder. Experimental results indicate that the proposed technique significantly outperforms not only the usual spatial-domain approach to mesh-based motion estimation and compensation, but also the emerging wavelet-based coders that employ traditional block-based structures, particularly for sequences with fast or complex motion.     

基于模糊量化和2 bit深度像素的运动估计算法

提出了一种2 bit深度像素的运动估计算法。首先,将像素深度的降采样过程形式化为区间分划和区间映射2个步骤,其中前者为多对一映射,决定着运动估计性能,后者为一一映射;其次,提出一种非均匀量化方法求解区间分划的3个初始阈值,并利用隶属度函数对初始阈值细化,从而克服信号噪声等因素导致的初始阈值周围像素值的误匹配;再次,讨论了适用于2 bit深度像素运动估计的误差度量准则,进而提出了基于模糊量化和2 bit深度像素的运动估计算法;最后,借助信号自相关函数,建立比特深度转换误差—运动向量精度模型来估计该算法所能达到的预测精度。实验结果证明,对于多种类型的视频序列,尤其是场景细节和物体运动比较复杂者,该算法始终能保持较高的估计精度,运动补偿的平均峰值信噪比较之传统2 bit深度像素的运动估计提高0.27 dB。     

多输入多输出正交频分复用中基于频域的信干噪比估计

终端的信干噪比(SINR)信息是多输入多输出正交频分复用(MIMO OFDM)系统进行编码调制方式选择和资源分配的重要依据之一。在频率选择性衰落信道中,针对MIMO OFDM的链路特征提出一种低复杂度的SINR估计方法:利用子载波之间的相关性构造降秩矩阵,提取其协方差矩阵的最小特征值来估计SINR,并分析了SINR估计误差。遵循LTE标准规范,进行了计算机仿真。结果表明:在SINR小于30 dB时,该方法只需要利用连续4个参考信号载波,便可实现估计误差小于0.2 dB,且该方法对最大多普勒频移不敏感。     

Motion estimation in the 3-D Gabor domain.

Motion estimation methods can be broadly classified as being spatiotemporal or frequency domain in nature. The Gabor representation is an analysis framework providing localized frequency information. When applied to image sequences, the 3-D Gabor representation displays spatiotemporal/spatiotemporal-frequency (st/stf) information, enabling the application of robust frequency domain methods with adjustable spatiotemporal resolution. In this work, the 3-D Gabor representation is applied to motion analysis. We demonstrate that piecewise uniform translational motion can be estimated by using a uniform translation motion model in the st/stf domain. The resulting motion estimation method exhibits both good spatiotemporal resolution and substantial noise resistance compared to existing spatiotemporal methods. To form the basis of this model, we derive the signature of the translational motion in the 3-D Gabor domain. Finally, to obtain higher spatiotemporal resolution for more complex motions, a dense motion field estimation method is developed to find a motion estimate for every pixel in the sequence.     

Motion estimation in ultrasound images using time domain cross correlation with prior estimates

In this paper we introduce a new speckle tracking method that is based on the standard time-domain cross correlation strain estimation (TDE). We call this method time-domain cross-correlation with prior estimates (TDPE), because it uses prior displacement estimates of neighboring windows to speed up computation. TDPE has all the advantages of TDE, but is much faster. Simulations, as well as experiments with phantoms and tissue, indicate that TDPE is capable of reliably estimating tissue displacement and strain over a large range of displacements in real time. The computational efficiency of TDPE is compared with current time-efficient methods that have been used in real time strain imaging systems. The results show that TDPE is the most time efficient algorithm to date, and is roughly 10 times faster than the TDE. The implementation of TDPE on an Ultrasonix RP500 ultrasound machine runs at 30 fps for strain images of 16 000 pixels.     

Maximum likelihood parameter estimation of F-ARIMA processes using the genetic algorithm in the frequency domain

This work aims to treat the parameter estimation problem for fractional-integrated autoregressive moving average (F-ARIMA) processes under external noise. Unlike the conventional approaches from the perspective of the time domain, a maximum likelihood (ML) method is developed in the frequency domain since the power spectrum of an F-ARIMA process is in a very explicit and more simple form. However, maximization of the likelihood function is a highly nonlinear estimation problem. Conventional searching algorithms are likely to converge to local maxima under this situation. Since the genetic algorithm (GA) tends to find the globally optimal solution without being trapped at local maxima, an estimation scheme based on the GA is therefore developed to solve the ML parameter estimation problem for F-ARIMA processes from the frequency domain perspective. In the parameter estimation procedure, stability of the F-ARIMA model is ensured, and convergence to the global optimum of the likelihood function is also guaranteed. Finally, several simulation examples are presented to illustrate the proposed estimation algorithm and exhibit its performance.     

Iterative frequency domain channel estimation for dft-precoded ofdm systems using in-band pilots

We consider two techniques of in-band frequency domain multiplexed (FDM) pilots using interleaved frequency domain multiple access (IFDMA) signal with a Chu sequence for DFT-precoded OFDM (or single-carrier (SC)) systems. One, called frequency domain superimposed pilot technique (FDSPT), superimposes pilot tones onto scaled or deleted data tones, which preserves spectral efficiency at the expense of a slight performance loss. The other, called frequency expanding technique (FET), multiplexes pilot tones by displacing data tones, which slightly reduces spectral efficiency. Using FDM pilots in SC systems facilitates flexible and efficient assignment of signals to available spectrum. We propose an iterative frequency domain decision-directed interference cancellation technique to reduce the intersymbol interference level of SC signals with FDSPT pilots (resulting from the suppression of data tones). Moreover, we propose a low complexity frequency domain iterative decision-directed channel estimation (IDDCE) technique for SC systems using FDM pilots. Using IDDCE, the frame error rate (FER) performance for coded SC systems using FET and FDSPT pilots with interference cancellation is found to be about 0.2 dB and about 0.5 dB, respectively, away from the FER performance with known channel frequency response at FER=10^-2. FDSPT pilots can also be used for OFDM systems with channel coding. It is found that an extra 1 dB of SNR is required at FER=10^-2,compared with that using the conventional FET pilots for OFDM systems.     

Damped sinusoidal signals parameter estimation in frequency domain

Parameter estimation of noisy damped sinusoidal signals in the frequency domain is presented in this paper. The advantage of the frequency domain approach is having the spectral energy concentrated in frequency domain samples. However, the least squares criterion for frequency estimation using frequency domain samples is nonlinear. A low complexity three-sample estimation algorithm (TSEA) for solving the nonlinear problem is proposed. Using the TSEA for initialization, a frequency domain nonlinear least squares (FD-NLS) estimation algorithm is then proposed. In the case of white Gaussian noise, it yields maximum likelihood estimates, verified by simulation results. A time domain NLS (TD-NLS) estimation algorithm is also proposed for comparison.The Cramer-Rao lower bound (CRLB) of the frequency domain estimation algorithms is derived. The theoretical analysis shows that the FD-NLS can yield a near-optimal performance with few energy-concentrated samples. On the other hand, the TD-NLS does not have the energy concentration property and requires more time domain samples to perform satisfactory estimation. Simulation results verify that the frequency domain estimation algorithms provide better tradeoff between computational complexity and estimation accuracy than time domain algorithms.     

Motion estimation using higher order statistics

The objective of this paper is to introduce a fourth-order cost function of the displaced frame difference (DFD) capable of estimating motion even for small regions or blocks. Using higher than second-order statistics is appropriate in case the image sequence is severely corrupted by additive Gaussian noise. Some results are presented and compared to those obtained from the mean kurtosis and the mean square error of the DFD.     

Motion estimation processor using mixed-signal approach

This paper describes the design, realization, and evaluation of a mixed-signal motion estimation processor using the full-search block-matching algorithm. The approach features digital I/O and a low-power, compact analog computational core. The proof-of-concept realization whose architecture incorporates pixel reuse, was fabricated in 0.8-/spl mu/m CMOS technology occupying 0.65 mm/sup 2/, and operates on 4 /spl times/ 4 pixel blocks and a search area of 8 /spl times/ 8 pixels. The processor achieves a low energy consumption per motion vector of 1.35 nJ and dissipates 0.8 mW from a 3-V power supply at QCIF 15 frames/s. The approach is intended for portable applications of digital video encoding.     

Motion estimation algorithm using interblock correlation

A new motion estimation algorithm that exploits the motion correlation of neighbor blocks in temporal and spatial directions is presented. Preliminary results indicate that this algorithm achieves significant savings on computation time and the amount of side information on motion vectors.<>     

Motion blur kernel estimation in steerable gradient domain of decomposed image

Blind deblurring, typically underdetermined or ill-posed problem, has attracted numerous research studies over the recent years. Various priors of either the image or the blur kernel are proposed to establish various regularization models to estimate the blur kernel. And sharp edges are often employed as an important clue to recover the blur kernel. However, due to the harmful effects caused by textures and various artifacts, sharp edges are not always beneficial to the kernel estimation. To address this problem, this paper presents a step-edge based blind image deblurring algorithm using steerable gradients. The proposed algorithm adopts a coarse-to-fine multiscale framework with step-edge restoration, kernel estimation and latent image estimation. In each scale, the step-edges are detected and refined through fast image decomposition and thresholding on steerable gradients, while the kernel and latent image are estimated by minimizing the quadratic energy functionals with steerable gradients. Because each of the minimizing functional has a closed-form solution, and can be implemented by using FFTs, our algorithm is also very fast. Experimental results on both synthetic and real data demonstrate that our method outperforms most existing single image blind deblurring methods.     

MIMO-OFDM系统中基于空频域导频的信道估计

讨论了MIMO-OFDM系统中基于空频域导频的信道估计,使用了LS方法估计导频点处的信道响应,再使用线性内插算法得到信道的全响应.同时为了有效地减小由内插和噪声所引起的误差,提出了在线性内插后设置一个由IFFT/FFT模块实现的低通滤波器,仿真结果表明改进后的系统能有效地去除噪声,使系统误码率改善了1dB左右.此结论验证了此方案的有效性.     

Channel estimation in space and frequency domain for MIMO-OFDM systems

Multiple-input multiple-output (MIMO) systems can be combined with orthogonal frequency division multiplexing (OFDM) systems to improve the capacity and quality of wireless communications. In this article, a channel estimation technique in both space and frequency domain for MIMO-OFDM systems is proposed. It is shown that the proposed scheme with space-frequency pilot tones achieve optimal minimum mean square error (MMSE) channel estimation. Simulation results indicate that the proposed method achieves good performance.     

Motion parameter estimation by using time-frequency representations

The estimation of motion parameters of moving objects by using variable μ-propagation and time-frequency representations is proposed. The spectrogram and the Wigner distribution, two basic time-frequency distributions, are used. Both the velocity and the initial position can be accurately estimated by this approach     

Motion estimation using a complex-valued wavelet transform

This paper describes a new motion estimation algorithm that is potentially useful for both computer vision and video compression applications. It is hierarchical in structure, using a separable two-dimensional (2-D) discrete wavelet transform (DWT) on each frame to efficiently construct a multiresolution pyramid of subimages. The DWT is based on a complex-valued pair of four-tap FIR filters with Gabor-like characteristics. The resulting complex DWT (CDWT) effectively implements an analysis by an ensemble of Gabor-like filters with a variety of orientations and scales. The phase difference between the subband coefficients of each frame at a given subpel bears a predictable relation to a local translation in the region of the reference frame subtended by that subpel. That relation is used to estimate the displacement field at the coarsest scale of the multiresolution pyramid. Each estimate is accompanied by a directional confidence measure in the form of the parameters of a quadratic matching surface. The initial estimate field is progressively refined by a coarse-to fine strategy in which finer scale information is appropriately incorporated at each stage. The accuracy, efficiency, and robustness of the new algorithm are demonstrated in comparison testing against hierarchical implementations of intensity gradient-based and fractional-precision block matching motion estimators     

快速菱形搜索运动估计方法

提出一种快速菱形运动估计算法,利用运动矢量的中心偏移特性,在第一步搜索时设立一个门限值,减小获得运动矢量所需的搜索次数。实验结果表明,算法在降低计算复杂度的同时,保持了较好的图像质量。     

Performance study of gradient correlation for sub-pixel motion estimation in the frequency domain

The authors present a performance study of gradient correlation in the context of the estimation of interframe motion in video sequences. The method is based on the maximisation of the spatial gradient cross-correlation function, which is computed in the frequency domain and therefore can be implemented by fast transformation algorithms. Enhancements to the baseline gradient-correlation algorithm are presented which further improve performance, especially in the presence of noise. A comparative performance study is also presented, which demonstrates that the proposed method outperforms state-of-the-art methods in frequency-domain motion estimation, in the shape of phase correlation, in terms of sub-pixel accuracy for a range of test material and motion scenarios.     

一种基于频域的转动惯量估算方法

描述了控制对象的两种等效数学模型,以第二种数学模型作为被控对象.引入了电流校正环节,建立了基于电流闭环的速度开环传递函数,推导了关于该速度开环传递函数的数学不等式,再将实际测得的幅频特性代入此不等式中,得到了关于转动惯量和机械时间常数的数学表达式.最后,以某光电测量设备的垂直轴作为控制对象进行了实验,用动态信号分析仪SR785测得实际系统的幅频特性,将该特性曲线上的某频率点代入到所建立的速度开环传递函数不等式中,得到转动惯量大于116.5590、小于116.609 7;机械时间常数大于0.561 587、小于0.561 638.由此可见,这种基于速度开环频域特性估算系统转动惯量和机械时间常数的方法是相当准确的.     

Motion estimation for video compression using Kalman filtering

Motion estimation plays an important role for the compression of video signals. This paper presents a new block-based motion estimation method using Kalman filtering. The new method utilizes the predicted motion and measured motion to obtain an optimal estimate of motion vector. The autoregressive models are employed to fit the motion correlation between neighboring blocks and then achieve predicted motion information. The measured motion information is obtained by the conventional block-based fast search schemes. Several algorithms based on either one- or two dimensional models using either nonadaptive or adaptive Kalman filters are developed. The analysis of computational complexity and the simulation results indicate that the proposed method achieves significant savings on computation along with smoother motion vector fields and similar picture quality, when compared to the conventional full search algorithm