Fast Haar Transform Based Feature Extraction for Face Representation and Recognition

Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications and additions, which makes the projection process computationally expensive. To tackle this problem, this paper proposes two simple-but-effective fast subspace learning and image projection methods, fast Haar transform (FHT) based principal component analysis and FHT based spectral regression discriminant analysis. The advantages of these two methods result from employing both the FHT for subspace learning and the integral vector for feature extraction. Experimental results on three face databases demonstrated their effectiveness and efficiency.

Efficient HOG human detection

While Histograms of Oriented Gradients (HOG) plus Support Vector Machine (SVM) (HOG+SVM) is the most successful human detection algorithm, it is time-consuming. This paper proposes two ways to deal with this problem. One way is to reuse the features in blocks to construct the HOG features for intersecting detection windows. Another way is to utilize sub-cell based interpolation to efficiently compute the HOG features for each block. The combination of the two ways results in significant increase in detecting humans-more than five times better. To evaluate the proposed method, we have established a top-view human database. Experimental results on the top-view database and the well-known INRIA data set have demonstrated the effectiveness and efficiency of the proposed method. (C) 2010 Elsevier B.V. All rights reserved.

快速模糊边缘检测算法

通过对Pal.King的模糊边缘检测算法进行改进，提出了一种快速模糊边缘检测算法。该快速算法不但简化了Pal.King算法中复杂的G和G-1运算，而且通过实验，确定了Tr变换中最佳的隶属度阈值，大大地减少了迭代次数。从实验结果中可以看出，该快速算法不但提高了Pal.King算法的效率，而且具有很强的检测模糊边缘和细小边缘的能力。这种快速算法的性能优越，是一种非常实用的、高效的的图像处理算法。

高阶广义屏波动方程叠前深度偏移

Attaining sufficient accuracy and efficiency of generalized screen propagator and improving the quality of input gathers are often problems　of wave equation presack depth migration,　in this paper,a high order formula of generalized screen propagator　for one-way wave equation is proposed by using the asymptotic expansion of single-square-root operator. Based on the formula，a new generalized screen propagator is developed ,which is composed of split-step Fourier propagator and high order correction terms，the new generalized screen propagator not only improving calculation precision without sharply increasing the quantity of computation，facilitates the suitability of generalized screen propagator to the media with strong lateral velocity variation.　As wave-equation prestack depth migration is sensitive to the quality of input gathers, which greatly affect the output，and the available seismic data processing system has inability to obtain traveltimes corresponding to the multiple arrivals, to estimate of great residual statics， to merge seismic datum from different projects and to design inverse Q filter, we establish　difference equations with an embodiment of Huygens’s principle for obtaining traveltimes corresponding to the multiple arrivals,bring forward a time variable matching filter for seismic datum merging by using the fast algorithm called Mallat tree for wavelet transformations， put forward a method for estimation of residual statics by applying the optimum model parameters estimated by iterative inversion with three organized algorithm,i.e,the CMP intertrace cross-correlation algorithm,the Laplacian image edge extraction algorithm,and the DFP algorithm, and present phase-shift inverse Q filter based on Futterman’s amplitude and phase-velocity dispersion formula and wave field extrapolation theory. All of their numerical and real data calculating results shows that our theory and method are practical and efficient. Key words: prestack depth migration, generalized screen propagator, residual statics，inverse Q filter ,traveltime，3D seismic datum mergence

Fourier有限差分法深度偏移与正演模拟

With the development of seismic exploration, the target becomes more and more complex, which leads to a higher demand for the accuracy and efficiency in 3D exploration. Fourier finite-difference (FFD) method is one of the most valuable methods in complex structure exploration, which keeps the ability of finite-differenc method in dealing with laterally varing media and inherits the predominance of the phase-screen method in stablility and efficiency. In this thesis, the accuracy of the FFD operator is highly improved by using simulated annealing algorithm. This method takes the extrapolation step and band width into account, which is more suitable to various band width and discrete scale than the commonely-used optimized method based on velocity contrast alone. In this thesis, the FFD method is extended to viscoacoustic modeling. Based on one-way wave equation, the presented method is implemented in frequency domain; thus, it is more efficient than two-way methods, and is more convenient than time domain methods in handling attenuation and dispersion effects. The proposed method can handle large velocity contrast and has a high efficiency, which is helpful to further research on earth absorption and seismic resolution. Starting from the frequency dispersion of the acoustic VTI wave equation, this thesis extends the FFD migration method to the acoustic VTI media. Compared with the convetional FFD method, the presented method has a similar computational efficiency, and keeps the abilities of dealing with large velocity contrasts and steep dips. The numerical experiments based on the SEG salt model show that the presented method is a practical migration method for complex acoustical VTI media, because it can handle both large velocity contrasts and large anisotropy variations, and its accuracy is relatively high even in strong anisotropic media. In 3D case, the two-way splitting technique of FFD operator causes artificial azimuthal anisotropy. These artifacts become apparent with increasing dip angles and velocity contrasts, which prevent the application of the FFD method in 3D complex media. The current methods proposed to reduce the azimuthal anisotropy significantly increase the computational cost. In this thesis, the alternating-direction-implicit plus interpolation scheme is incorporated into the 3D FFD method to reduce the azimuthal anisotropy. By subtly utilizing the Fourier based scheme of the FFD method, the improved fast algorithm takes approximately no extra computation time. The resulting operator keeps both the accuracy and the efficiency of the FFD method, which is helpful to the inhancements of both the accuracy and the efficiency for prestack depth migration. The general comparison is presented between the FFD operator and the generalized-screen operator, which is valuable to choose the suitable method in practice. The percentage relative error curves and migration impulse responses show that the generalized-screen operator is much sensiutive to the velocity contrasts than the FFD operator. The FFD operator can handle various velocity contrasts, while the generalized-screen operator can only handle some range of the velocity contrasts. Both in large and weak velocity contrasts, the higher order term of the generalized-screen operator has little effect on improving accuracy. The FFD operator is more suitable to large velocity contrasts, while the generalized-screen operator is more suitable to middle velocity contrasts. Both the one-way implicit finite-difference migration and the two-way explicit finite-differenc modeling have been implemented, and then they are compared with the corresponding FFD methods respectively. This work gives a reference to the choosen of proper method. The FFD migration is illustrated to be more attractive in accuracy, efficiency and frequency dispertion than the widely-used implicit finite-difference migration. The FFD modeling can handle relatively coarse grids than the commonly-used explicit finite-differenc modeling, thus it is much faster in 3D modeling, especially for large-scale complex media.

基于匹配追踪方法的地震信号时频分析研究

Seismic signal is a typical non-stationary signal, whose frequency is continuously changing with time and is determined by the bandwidth of seismic source and the absorption characteristic of the media underground. The most interesting target of seismic signal’s processing and explaining is to know about the local frequency’s abrupt changing with the time, since this kind of abrupt changing is indicating the changing of the physical attributes of the media underground. As to the seismic signal’s instantaneous attributes taken from time-frequency domain, the key target is to search a effective, non-negative and fast algorithm time-frequency distribution, and transform the seismic signal into this time-frequency domain to get its instantaneous power spectrum density, and then use the process of weighted adding and average etc. to get the instantaneous attributes of seismic signal. Time-frequency analysis as a powerful tool to deal with time variant non-stationary signal is becoming a hot researching spot of modern signal processing, and also is an important method to make seismic signal’s attributes analysis. This kind of method provides joint distribution message about time domain and frequency domain, and it clearly plots the correlation of signal’s frequency changing with the time. The spectrum decomposition technique makes seismic signal’s resolving rate reach its theoretical level, and by the method of all frequency scanning and imaging the three dimensional seismic data in frequency domain, it improves and promotes the resolving abilities of seismic signal vs. geological abnormal objects. Matching pursuits method is an important way to realize signal’s self-adaptive decomposition. Its main thought is that any signal can be expressed by a series of time-frequency atoms’ linear composition. By decomposition the signal within an over completed library, the time-frequency atoms which stand for the signal itself are selected neatly and self-adaptively according to the signal’s characteristics. This method has excellent sparse decomposition characteristics, and is widely used in signal de-noising, signal coding and pattern recognizing processing and is also adaptive to seismic signal’s decomposition and attributes analysis. This paper takes matching pursuits method as the key research object. As introducing the principle and implementation techniques of matching pursuits method systematically, it researches deeply the pivotal problems of atom type’s selection, the atom dictionary’s discrete, and the most matching atom’s searching algorithm, and at the same time, applying this matching pursuits method into seismic signal’s processing by picking-up correlative instantaneous messages from time-frequency analysis and spectrum decomposition to the seismic signal. Based on the research of the theory and its correlative model examination of the adaptively signal decomposition with matching pursuit method, this paper proposes a fast optimal matching time-frequency atom’s searching algorithm aimed at seismic signal’s decomposition by frequency-dominated pursuit method and this makes the MP method pertinence to seismic signal’s processing. Upon the research of optimal Gabor atom’s fast searching and matching algorithm, this paper proposes global optimal searching method using Simulated Annealing Algorithm, Genetic Algorithm and composed Simulated Annealing and Genetic Algorithm, so as to provide another way to implement fast matching pursuit method. At the same time, aimed at the characteristics of seismic signal, this paper proposes a fast matching atom’s searching algorithm by means of designating the max energy points of complex seismic signal, searching for the most optimal atom in the neighbor area of these points according to its instantaneous frequency and instantaneous phase, and this promotes the calculating efficiency of seismic signal’s matching pursuit algorithm. According to these methods proposed above, this paper implements them by programmed calculation, compares them with some open algorithm and proves this paper’s conclusions. It also testifies the active results of various methods by the processing of actual signals. The problems need to be solved further and the aftertime researching targets are as follows: continuously seeking for more efficient fast matching pursuit algorithm and expanding its application range, and also study the actual usage of matching pursuit method.

Parallel optical negabinary signed-digit computing: algorithm and optical implementation

Negabinary is a component of the positional number system. A complete set of negabinary arithmetic operations are presented, including the basic addition/subtraction logic, the two-step carry-free addition/subtraction algorithm based on negabinary signed-digit (NSD) representation, parallel multiplication, and the fast conversion from NSD to the normal negabinary in the carry-look-ahead mode. All the arithmetic operations can be performed with binary logic. By programming the binary reference bits, addition and subtraction can be realized in parallel with the same binary logic functions. This offers a technique to perform space-variant arithmetic-logic functions with space-invariant instructions. Multiplication can be performed in the tree structure and it is simpler than the modified signed-digit (MSD) counterpart. The parallelism of the algorithms is very suitable for optical implementation. Correspondingly, a general-purpose optical logic system using an electron trapping device is suggested. Various complex logic functions can be performed by programming the illumination of the data arrays without additional temporal latency of the intermediate results. The system can be compact. These properties make the proposed negabinary arithmetic-logic system a strong candidate for future applications in digital optical computing with the development of smart pixel arrays. (C) 1999 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(99)00803-X].

A reliable phase unwrapping algorithm based on the local fitting plane and quality map

A fast and reliable phase unwrapping (PhU) algorithm, based on the local quality-guided fitting plane, is presented. Its framework depends on the basic plane-approximated assumption for phase values of local pixels and on the phase derivative variance (PDV) quality map. Compared with other existing popular unwrapping algorithms, the proposed algorithm demonstrated improved robustness and immunity to strong noise and high phase variations, given that the plane assumption for local phase is reasonably satisfied. Its effectiveness is demonstrated by computer-simulated and experimental results.

Application of fast Pade approximation in simulating photonic crystal nanocavities by FDTD technology

The exact calculation of mode quality factor Q is a key problem in the design of high-Q photonic crystal nanocavity. On the basis of further investigation on conventional Pade approximation, FDM and DFT, Pade approximation with Baker's algorithm is enhanced through introducing multiple frequency search and parabola interpolation. Though Pade approximation is a nonlinear signal processing method and only short time sequence is needed, we find the different length of sequence requirements for 2D and 3D FDTD, which is very important to obtain convergent and accurate results. By using the modified Pade approximation method and 3D FDTD, the 2D slab photonic crystal nanocavity is analyzed and high-Q multimode can be solved quickly instead of large range high-resolution scanning. Monitor position has also been investigated. These results are very helpful to the design of photonic crystal nanocavity devices. (C) 2008 Elsevier B.V. All rights reserved.

Compact non-binary fast adders using single-electron devices

This paper proposes compact adders that are based on non-binary redundant number systems and single-electron (SE) devices. The adders use the number of single electrons to represent discrete multiple-valued logic state and manipulate single electrons to perform arithmetic operations. These adders have fast speed and are referred as fast adders. We develop a family of SE transfer circuits based on MOSFET-based SE turnstile. The fast adder circuit can be easily designed by directly mapping the graphical counter tree diagram (CTD) representation of the addition algorithm to SE devices and circuits. We propose two design approaches to implement fast adders using SE transfer circuits the threshold approach and the periodic approach. The periodic approach uses the voltage-controlled single-electron transfer characteristics to efficiently achieve periodic arithmetic functions. We use HSPICE simulator to verify fast adders operations. The speeds of the proposed adders are fast. The numbers of transistors of the adders are much smaller than conventional approaches. The power dissipations are much lower than CMOS and multiple-valued current-mode fast adders. (C) 2009 Elsevier Ltd. All rights reserved.

A Novel Architecture of Vision Chip for Fast Traffic Lane Detection and FPGA Implementation

This paper presents a novel architecture of vision chip for fast traffic lane detection (FTLD). The architecture consists of a 32*32 SIMD processing element (PE) array processor and a dual-core RISC processor. The PE array processor performs low-level pixel-parallel image processing at high speed and outputs image features for high-level image processing without I/O bottleneck. The dual-core processor carries out high-level image processing. A parallel fast lane detection algorithm for this architecture is developed. The FPGA system with a CMOS image sensor is used to implement the architecture. Experiment results show that the system can perform the fast traffic lane detection at 50fps rate. It is much faster than previous works and has good robustness that can operate in various intensity of light. The novel architecture of vision chip is able to meet the demand of real-time lane departure warning system.

Application of the Conjugate Gradient Optimization Algorithm of Neural Network on Laser Machining

在应用激光技术加工复杂曲面时,通常以采样点集为插值点来建立曲面函数,然后实现曲面上任意坐标点的精确定位。人工神经网络的BP算法能实现函数插值,但计算精度偏低,往往达不到插值精确要求,造成较大的加工误差。提出人工神经网络的共轭梯度最优化插值新算法,并通过实例仿真,证明了这种曲面精确定位方法的可行性,从而为激光加工的三维精确定位提供了一种良好解决方案。这种方法已经应用在实际中。