Vehicle detection in aerial surveillance using dynamic Bayesian networks

We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.     

Spectral-spatial classification of hyperspectral data based on a stochastic minimum spanning forest approach

In this paper, a new method for supervised hyperspectral data classification is proposed. In particular, the notion of stochastic minimum spanning forest (MSF) is introduced. For a given hyperspectral image, a pixelwise classification is first performed. From this classification map, M marker maps are generated by randomly selecting pixels and labeling them as markers for the construction of MSFs. The next step consists in building an MSF from each of the M marker maps. Finally, all the M realizations are aggregated with a maximum vote decision rule in order to build the final classification map. The proposed method is tested on three different data sets of hyperspectral airborne images with different resolutions and contexts. The influences of the number of markers and of the number of realizations M on the results are investigated in experiments. The performance of the proposed method is compared to several classification techniques (both pixelwise and spectral-spatial) using standard quantitative criteria and visual qualitative evaluation.     

Classification with spatio-temporal interpixel class dependencycontexts

A contextual classifier which can utilize both spatial and temporal interpixel dependency contexts is investigated. After spatial and temporal neighbors are defined, a general form of maximum a posterior spatiotemporal contextual classifier is derived. This contextual classifier is simplified under several assumptions. Joint prior probabilities of the classes of each pixel and its spatial neighbors are modeled by the Gibbs random field. The classification is performed in a recursive manner to allow a computationally efficient contextual classification. Experimental results with bitemporal TM data show significant improvement of classification accuracy over noncontextual pixelwise classifiers. This spatiotemporal contextual classifier should find use in many applications of remote sensing, especially when the classification accuracy is important     

Cross residual transform for lossless intra-coding for HEVC

A new lossless intra-coding method based on a cross residual transform is applied to the next generation video coding standard HEVC (High Efficiency Video Coding). HEVC includes a multi-directional spatial prediction method to reduce spatial redundancy by using neighboring pixels as a prediction for the pixels in a block of data to be encoded. In the new lossless intra-coding method, the spatial prediction is performed as pixelwise DPCM but is implemented as block-based manner by using cross residual transform on the HEVC standard. The experimental results show that the new lossless intra-coding method reduces the bit rate of approximately 8.43% in comparison with the lossless-intra coding method in the HEVC standard and the proposed method results in slightly better compression ratio than the JPEG200 lossless coding.     

Model-based segmentation of medical imagery by matching distributions

The segmentation of deformable objects from three-dimensional (3-D) images is an important and challenging problem, especially in the context of medical imagery. We present a new segmentation algorithm based on matching probability distributions of photometric variables that incorporates learned shape and appearance models for the objects of interest. The main innovation over similar approaches is that there is no need to compute a pixelwise correspondence between the model and the image. This allows for a fast, principled algorithm. We present promising results on difficult imagery for 3-D computed tomography images of the male pelvis for the purpose of image-guided radiotherapy of the prostate.     

Pixelwise-adaptive blind optical flow assuming nonstationary statistics.

In this paper, we address some of the major issues in optical flow within a new framework assuming nonstationary statistics for the motion field and for the errors. Problems addressed include the preservation of discontinuities, model/data errors, outliers, confidence measures, and performance evaluation. In solving these problems, we assume that the statistics of the motion field and the errors are not only spatially varying, but also unknown. We, thus, derive a blind adaptive technique based on generalized cross validation for estimating an independent regularization parameter for each pixel. Our formulation is pixelwise and combines existing first- and second-order constraints with a new second-order temporal constraint. We derive a new confidence measure for an adaptive rejection of erroneous and outlying motion vectors, and compare our results to other techniques in the literature. A new performance measure is also derived for estimating the signal-to-noise ratio for real sequences when the ground truth is unknown.     

一种高分辨率遥感影像分类的特征指数

随着影像分辨率的提高,传统的光谱特征不能有效地描述复杂的高分辨率影像信息,从而影响高分辨率遥感影像的分类。为了弥补传统光谱方法的不足,提出了一种加权对象相关指数(WOCI),并将其应用到基于支持向量机(SVM)的影像分类中。该指数是通过考虑具有相似性光谱的对象来构建的,可全面地描述影像的上下文结构。结果表明与仅考虑光谱特征和像素空间特征进行分类的方法相比,基于WOCI特征的分类结果有更高的精确性,且分类精度提高了7.16%。     

Perceptual similarity between color images using fuzzy metrics

In many applications of the computer vision field measuring the similarity between (color) images is of paramount importance. However, the commonly used pixelwise similarity measures such as Mean Absolute Error, Peak Signal to Noise Ratio, Mean Squared Error or Normalized Color Difference do not match well with perceptual similarity. Recently, it has been proposed a method for gray-scale image similarity that correlates quite well with the perceptual similarity and it has been extended to color images. In this paper we use the basic ideas in this recent work to propose an alternative method based on fuzzy metrics for perceptual color image similarity. Experimental results employing a survey of observations show that the global performance of our proposal is competitive with best state of the art methods and that it shows some advantages in performance for images with low correlation among some image channels.     

A multiplicative iterative algorithm for box-constrained penalized likelihood image restoration

Image restoration is a computationally intensive problem as a large number of pixel values have to be determined. Since the pixel values of digital images can attain only a finite number of values (e.g., 8-bit images can have only 256 gray levels), one would like to recover an image within some dynamic range. This leads to the imposition of box constraints on the pixel values. The traditional gradient projection methods for constrained optimization can be used to impose box constraints, but they may suffer from either slow convergence or repeated searching for active sets in each iteration. In this paper, we develop a new box-constrained multiplicative iterative (BCMI) algorithm for box-constrained image restoration. The BCMI algorithm just requires pixelwise updates in each iteration, and there is no need to invert any matrices. We give the convergence proof of this algorithm and apply it to total variation image restoration problems, where the observed blurry images contain Poisson, Gaussian, or salt-and-pepper noises.     

Adaptive Bayesian contextual classification based on Markov random fields

An adaptive Bayesian contextual classification procedure that utilizes both spectral and spatial interpixel dependency contexts in estimation of statistics and classification is proposed. Essentially, this classifier is the constructive coupling of an adaptive classification procedure and a Bayesian contextual classification procedure. In this classifier, the joint prior probabilities of the classes of each pixel and its spatial neighbors are modeled by the Markov random field. The estimation of statistics and classification are performed in a recursive manner to allow the establishment of the positive-feedback process in a computationally efficient manner. Experiments with real hyperspectral data show that, starting with a small training sample set, this classifier can reach classification accuracies similar to that obtained by a pixelwise maximum likelihood pixel classifier with a very large training sample set. Additionally, classification maps are produced that have significantly less speckle error.     

在SOI基上设计实现D/A驱动的高压LDMOS开关电路

设计实现SOI基上带有D/A驱动的高压LDMOS功率开关电路,利用D/A变换的灵活性,运用数字电路与高压模拟电路混合设计方法,实现数字控制的耐压为300V的LDMOS功率开关电路．该功率集成电路芯片的实现,为SOI高压功率开关电路提供了一种更为方便快速的数字控制设计方法,同时也为功率系统集成电路提供了一种有效的实验验证,从而证实了功率系统集成的探索在理论上以及工程上具有一定的可行性．     

基于聚类识别的极化SAR图像分类

This paper presents a novel unsupervised image classification method for Polarimetric Synthetic Aperture Radar (PolSAR) data. The proposed method is based on a discriminative clustering framework that explicitly relies on a discriminative supervised classification technique to perform unsupervised clustering. To implement this idea, an energy function is designed for unsupervised PolSAR image classification by combining a supervised Softmax Regression (SR) model with a Markov Random Field (MRF) smoothness constraint. In this model, both the pixelwise class labels and classifiers are taken as unknown variables to be optimized. Starting from the initialized class labels generated by Cloude-Pottier decomposition and K-Wishart distribution hypothesis, the classifiers and class labels are iteratively optimized by alternately minimizing the energy function with respect to them. Finally, the optimized class labels are taken as the classification result, and the classifiers for different classes are also derived as a side effect. This approach is applied to real PolSAR benchmark data. Extensive experiments justify that the proposed approach can effectively classify the PolSAR image in an unsupervised way and produce higher accuracies than the compared state-of-the-art methods.     

具有有源下拉电路和图腾柱式输出结构的CML门电路

本文提出了一种高速低功耗、具有有源下拉电路和图腾柱式输出结构的ＣＭＬ（简称ＭＣＭＬ）门电路；详细地阐述了ＭＣＭＬ门电路的工作原理和优点；列出了电路仿真结果；并对其电路特性与ＥＣＬ和ＡＰＤ－ＥＣＬ电路进行了比较。     

Synthesis of Bashkow's a matrix for the general RC circuit

For many uses, a convenient formulation for solving a circuit is Bashkow's A matrix. The circuit formulation then becomes x? = Ax. Given this circuit formulation, the synthesis of a circuit for a particular A matrix is of interest. Such a synthesis is accomplished by finding the diagonalising matrix for A, finding the form of the square incidence submatrix for a general tree in this case, and then using a linear-programming technique.     

New synthesis method for a branch-line 3 dB hybrid: a hybridapproach comprising planar and transmission line circuit concepts

A synthesis method for a stripline-type branch-line 3-dB hybrid which is based on an equivalent circuit derived by the planar circuit approach is presented. The equivalent circuit of an ideal 3-dB hybrid is derived first from those of the segmented circuit elements, i.e., four three-port junctions and four quarter-wave transmission lines. A systematic synthesis process is then developed upon the basis of the equivalent circuit. Practical hybrid circuit having optimized circuit patterns which were constructed for center frequencies of 3, 5, and 7 GHz are discussed. Their measured characteristics are described. The results are shown to agree well with the theory     

Design of high-efficiency RF Class-D power amplifier

In this paper, the losses in a Class-D RF switching power amplifier and their frequency dependence are described. The losses analyzed are the switching, conduction, and gate drive losses. A 300 W, 13.56 MHz, Class-D circuit is designed in the traditional manner to illustrate the magnitude of the different types of loss. A circuit using the ZVS equations developed in this paper is designed. An experimental circuit is built using standard IRF540 devices in TO220 packages. That circuit does not meet its performance goals because of the package inductance. A new low inductance half-bridge package is introduced to solve this problem. Techniques for circuit layout and power measurements for RF applications are also presented in the experimental section. A low loss gate drive circuit is also presented using a Class-E circuit to provide the drive power. The experimental results confirm the accuracy of the design equations derived in this paper     

DES密码电路的抗差分功耗分析设计

提出一种互补结构的寄存器电路设计方案，用于减小DES加密电路的差分功率信号，防御差分功耗分析．提出了一种误导攻击者的干扰电路，在保证加密电路安全等级的前提下，大幅度降低了电路的硬件开销．为节约成本与缩短设计周期，文中使用了一套高效的抗攻击电路的设计流程．     

基于ASTLC5301A的TFT LCD栅驱动芯片研究

分析薄膜晶体管液晶显示（TFT-LCD）栅驱动芯片ASTLC5301A的原理，借助Pspice仿真工具进行驱动电路的设计，重点讨论芯片内部高低电平位移转换电路，提出改进型电平接口电路．完成高低压驱动管的尺寸和结构设计。     

Walk error minimisation by resonance-based laser pulse timing detection

A method for timing point detection in a laser pulse is presented. A pulse shaping circuit is placed at the input of the receiver to achieve a large dynamic range without gain control and timing errors caused by signal clipping. A parallel resonant circuit is proposed as the shaping circuit.     

基于ASTLC5301A的TFTLCD栅驱动芯片研究

分析薄膜晶体管液晶显示(TFT-LCD)栅驱动芯片ASTLC5301A的原理,借助Pspice仿真工具进行驱动电路的设计,重点讨论芯片内部高低电平位移转换电路,提出改进型电平接口电路,完成高低压驱动管的尺寸和结构设计。