Adaptive image enhancement based on clustering of wavelet coefficients for infrared sea surveillance systems

Most of the techniques developed for infrared (IR) image enhancement (IE) depend heavily on the scene, environmental conditions, and the properties of the imaging system. So, with a set of predefined scenario properties, a content-based IR-IE technique can be developed for better situational awareness. This study proposes an adaptive IR-IE technique based on clustering of wavelet coefficients of an image for sea surveillance systems. Discrete wavelet transform (DWT) of an image is computed and feature vectors are constructed from subband images. Clustering operation is applied to group similar feature vectors that belong to different scene components such as target or background. Depending on the feature vectors, a weight is assigned to each cluster and these weights are used to compute gain matrices which are used to multiply wavelet coefficients for the enhancement of the original image. Enhancement results are presented and a comparison of the performance of the proposed algorithm is given through subjective tests with other well known frequency and histogram based enhancement techniques. The proposed algorithm outperforms previous ones in the truthfulness, detail visibility of the target, artificiality, and total quality criteria, while providing an acceptable computational load.     

Reputation-based network selection mechanism using game theory

Current and future wireless environments are based on the coexistence of multiple networks supported by various access technologies deployed by different operators. As wireless network deployments increase, their usage is also experiencing a significant growth. In this heterogeneous multi-technology multi-application multi-terminal multi-user environment users will be able to freely connect to any of the available access technologies. Network selection mechanisms will be required in order to keep mobile users “always best connected” anywhere and anytime. In such a heterogeneous environment, game theory techniques can be adopted in order to understand and model competitive or cooperative scenarios between rational decision makers. In this work we propose a theoretical framework for combining reputation-based systems, game theory and network selection mechanism. We define a network reputation factor which reflects the network’s previous behaviour in assuring service guarantees to the user. Using the repeated Prisoner’s Dilemma game, we model the user–network interaction as a cooperative game and we show that by defining incentives for cooperation and disincentives against defecting on service guarantees, repeated interaction sustains cooperation.     

Investigation of morphology selection for CBr_4-C_2Cl_6 alloy in three dimensions with multi-phase field method

With the multi-phase field model, the unidirectional solidification with constant velocity growth and variable velocity growth of the CBr4-C2Cl6 eutectic alloy is simulated in three dimensions. The simulated results with constant velocity growth show that with the increase of pulling velocity, the morphology of the CBr4-C2Cl6 alloy evolves in the sequence of lamellar merging →lamellar-rod transition→stable lamellar growth→oscillating growth→lamellar branching. A morphology selection map is established with ...     

电多极矩跃迁选择定则的对称分析

只有由群的对称性才可能导出每个不可约表示的对称性波函数, 即对称化基函数.也只有由群的对称性才可能导出电子状态跃迁的最一般选择定则 , 即电偶极跃迁E1, 电四极跃迁E2 和 电八极跃迁E3跃迁的选择原则. 本文以 和 为例, 导出电多积跃迁的选择原则. 角动量的选择定则只是特例. 并用方法SAC-CI/6-31G 计算了 H2O和 CC的基态以及其激发态的激发能和振子强度.本文只适合单光子过程. 计算都与理论相合.     

A new type SVM-projected SVM

Support vector machine (SVM), developed by Vapnik et al., is a new and promising technique for classification and regression and has been proved to be competitive with the best available learning machines in many applications. However, the classification speed of SVM is substantially slower than that of other techniques with similar generalization ability. A new type SVM named projected SVM (PSVM), which is a combination of feature vector selection (FVS) method and linear SVM (LSVM), is proposed in present paper. In PSVM, the FVS method is first used to select a relevant subset (feature vectors, FVs) from the training data, and then both the training data and the test data are projected into the subspace constructed by FVs, and finally linear SVM(LSVM) is applied to classify the projected data. The time required by PSVM to calculate the class of new samples is proportional to the count of FVs. In most cases, the count of FVs is smaller than that of support vectors (SVs), and therefore PSVM is faster than SVM in running. Compared with other speeding-up techniques of SVM, PSVM is proved to possess not only speeding-up ability but also de-noising ability for high-noised data, and is found to be of potential use in mechanical fault pattern recognition.     

Nonlinear competition between asters and stripes in filament-motor systems

A model for polar filaments interacting via molecular motor complexes is investigated which exhibits bifurcations to spatial patterns. It is shown that the homogeneous distribution of filaments, such as actin or microtubules, may become either unstable with respect to an orientational instability of a finite wave number or with respect to modulations of the filament density, where long-wavelength modes are amplified as well. Above threshold nonlinear interactions select either stripe patterns or periodic asters. The existence and stability ranges of each pattern close to threshold are predicted in terms of a weakly nonlinear perturbation analysis, which is confirmed by numerical simulations of the basic model equations. The two relevant parameters determining the bifurcation scenario of the model can be related to the concentrations of the active molecular motors and of the filaments, respectively, which both could be easily regulated by the cell.     

鳀鱼(Engraulis japonicus)目标强度的模型法研究

采用声散射理论和目标强度近似模型评估法对黄海鲤鱼（Engraulis japonicus）的声散射特征和目标强度进行了数值计算与评估研究。散射模型由鱼鳔模型和鱼体模型两个部分构成，其中鱼鳔采用充满气体的椭球体模型，鳔除外的鱼体采用充满液体的椭球体模型。理论数值计算所需参数取自全长12．6cm的鲤鱼个体，其鱼鳔尺寸利用X光照片测得。平均目标强度利用模型算得的不同角度下的声散射强度与鲲鱼倾角分布函数的卷积计算，其中倾角（度）的分布函数设为N（-3．9，12．8^2）。结果显示，鲲鱼对声波的散射具有明显指向性；在38kHz和120kHz工作频率下，鲲鱼的最大背向目标强度分别为-41．2dB和-39．5dB，有效平均目标强度分别为-48．0dB和-51．5dB，与实测结果吻合较好。另外还对鲲鱼的反向散射指向性特征、目标强度的频率特征以及鱼鳔对鲲鱼整体目标强度的贡献等进行了分析与讨论。以上研究表明，模型法作为现场测定研究方法的重要补充和认知鱼类声学散射特性的有效途径，可在我国鱼类目标强度的研究中发挥重要作用。     

弹道相机白天工作能力的影响因素分析及提高途径

弹道相机通常是在夜间对飞行目标进行拍摄,在相机类型不改变的情况下要达到白天工作能力具有一定困难,主要障碍是拍摄后,底板上目标与背景的衬比(度)下降,难以达到判读要求.针对这一问题,本文详细叙述了各因素对判读要求的影响,提出了改善相机白天工作能力的可行方法.     

数码相机CMOS图像传感器的特性参数与选择

介绍了数码相机的核心器件———CMOS图像传感器的特性参数和在数码相机设计过程中CMOS图像传感器的选择。选择CMOS图像传感器,不仅需要考虑包括传感器的尺寸、像素总数和有效像素数、最小照度、动态范围、灵敏度、分辨力、光电响应不均匀性以及光谱响应等在内的特性参数,而且还要考虑电源管理和功耗、模数转换位数、开发的简便性以及成本等因素。     

浅谈杯鼓实验中空气柱的选频作用

本文首先通过杯鼓实验得到了不同空气柱长度下杯内声波的频域图,然后基于波动理论解析分析了边界振动有衰减时空气柱的共振频率及振幅,结果表明空气柱长度在声波传播过程中具有明显的选频作用。