Chan-Vese模型两相自适应窄带的阴影区检测方法

为得到快速高精度的声呐图像阴影区检测效果,提出Chan-Vese模型两相自适应窄带检测方法。利用各向异性二阶邻域马尔可夫模型估计声呐图像的纹理特征参数,实现原始图像平滑去噪;由块方式的k-均值聚类算法确定图像的初始两类分割,初步确定阴影区大致位置,并根据此大致位置,自适应初始化零水平集函数,来减少人为干预,提高检测速度;在此基础上,提出建立Chan-Vese模型两相窄带水平集进行声呐图像检测,完成局部寻优,排除全局图像中孤立区对检测的影响,使阴影区检测结果更加精确。通过对真实声呐图像的检测实验结果分析,验证提出的检测方法能够去除原始图像的部分噪声,提高检测精度和速度,有一定的自动性和适应性。     

旋流两相流动的DSM—PDF两相湍流模型

本文提出了气相雷诺应力方程模型和颗粒概率密度输运方程模型相结合而构成的ＤＳＭ—ＰＤＦ两相湍流模型,并用该模型和ｋ－ε－Ｋｐ模型模拟了文献中测量的旋流数为０．４７的旋流突扩气粒两相流动．和测量结果的对照表明,两模型都能较好地模拟族流数不高的两相流动平均速度场,但ＤＳＭ—ＰＤＦ模型可以揭示出两相湍流的各向异性,因此有预报强旋两相流动的潜力．     

DSM-LPDF两相湍流模型及旋流两相流动的模拟

本文由流体－颗粒速度的拉氏联合概率密度函数（ＰＤＦ）输运方程出发,用Ｓｉｍｏｎｉｎ建议的Ｌａｎｇｅｖｉｎ模型封闭颗粒所遇到流体瞬时速度的条件期望项,并用Ｍｏｎｔｅ Ｃａｒｌｏ方法直接求解 ＰＤＦ输运方程,将其和求解流体雷诺应力方程模型的有限差分方法结合,建立了雷诺应力－拉氏ＰＤＦ（ＤＳＭ－ＬＰＤＦ,简称ＤＬ）两相湍流模型．用此模型模拟了旋流数为０．４７的突扩旋流气粒两相流动,并与文献中ＰＤＰＡ实验和用类似于单相流动湍流模型封闭方法的时平均统一二阶矩（ＵＳＭ）模型的预报进行了对比．     

混合工质两相区热力性质隐式拟合方法

本文通过建立混合工质制冷剂两相区热力性质的隐式拟合模型,给出了混合工质制冷剂两相区热力性质的隐式拟合、显式计算的方法,保证了物性计算的快速和稳定性。本文以美国国家标准局开发的程序REFPROP6.01的计算结果作为数据源,对R410A和R407C的两相区物性分别在工况范围64.77-3825.32kPa和43.62-3972.58kPa内进行了拟合。与数据源相比,得到的快速计算公式的最大相对计算误差在0.56％之内,平均误差在0.025％之内,计算速度较REFPROP6.01提高三个数量级。     

基于Lagrange方法封闭的两相湍流场方程模型

两相湍流场方程模型采用基于Euler方法的一阶矩方程,而二阶矩方程由Lagrange方法得到,新模型的封闭不需要附加其它假设.首先基于概率密度函数给出颗粒运动的连续方程和动量方程,其次由基于平均Langevin方程的Lagrange模型推导得到颗粒二阶矩方程,最终获得封闭的二阶矩模型.将新模型用于气固两相壁面射流的数值模拟,结果表明新模型合理有效.     

可压缩非守恒型两相流模型的GKS方法

提出一种求解BN非守恒型两相流模型的方法.从微观角度出发,构造与BN模型相匹配的Gas-kineticscheme(GKS),通过对粒子速度分布函数积分求矩得到通量,把非守恒项直接包含到数值通量的演化和构造中,较好地处理了方程中包含的非守恒项.数值试验说明本方法的有效性.     

多孔介质内受迫对流凝结时两相共存区的非达西模型

本文提出多孔介质内受迫对流凝结时两相共存区的二维非达西流模型。分析了蒸气在多孔介质内沿水平平板和填充国管内受迫对流凝结时两相共存区的厚度。假定局部平衡和暂先假设蒸气为理想气体，化简了能量方程。     

气固两相各向同性湍流的自适应网格模拟

气固两相湍流是一个复杂的多尺度,多物理场的难题.为了捕捉流场的小尺度涡以及其对颗粒的作用,传统上采用了静态的高分辨率网格,消耗极大的计算资源.本文基于小波算法对网格进行加密或疏化,从而实现网格的自适应.基于自适应网格的框架上,建立颗粒与流场分块的映射,搭建了欧拉-拉格朗日的气固两相流模拟的并行平台.通过对均匀各向同性湍...     

基于Chan-Vese模型与形态学的医学图像分割算法

针对传统的多相Chan-Vese模型在进行多区域分割时容易产生空相位的问题,提出了一种改进的新的医学图像分割算法;该算法结合Chan-Vese模型、数学形态学、复合多相水平集分割算法,通过迭代腐蚀操作提取医学图像的轮廓,利用添加了复合多相水平集算法的Chan-Vese模型对医学图像进行分割,通过迭代膨胀操作复原图像;实验结果和分析表明,采用该算法很好地解决了医学图像分割过程中容易出现的多区域分割问题,减少了空相位的产生,而且对图像边缘有很好的分割效果。     

耦合界面力的两相流相场格子Boltzmann模型

提出了一种改进的基于相场理论的两相流格子Boltzmann模型.通过引入一种新的更加简化的外力项分布函数,使得此模型克服了前人工作中界面力尺度与理论分析不一致的问题,并且通过Chapman-Enskog多尺度分析表明,所提出的模型能够准确恢复到追踪界面的Cahn-Hilliard方程和不可压的Navier-Stokes方程,并且宏观速度的计算更为简化.利用所提模型对几个经典两相流问题,包括静态液滴测试、液滴合并问题、亚稳态分解以及瑞利-泰勒不稳定性进行了数值模拟,发现本模型可以获得量级为10^-9极小的虚假速度,并且这些算例获取的数值解与解析解或已有的文献结果相吻合,从而验证了模型的准确性和可行性.最后,利用所发展的两相流格子Boltzmann模型研究了随机扰动的瑞利-泰勒不稳定性问题,并着重分析了雷诺数对流体相界面的影响.发现对于高雷诺数情形,在演化前期,流体界面出现一排“蘑菇”形状,而在演化后期,流体界面呈现十分复杂的混沌拓扑结构.不同于高雷诺数情形,低雷诺数时流体界面变得相对光滑,在演化后期未观察到混沌拓扑结构.     

Shadow regions detection algorithm by adaptive narrowband two-phase Chan-Vese model

An adaptive narrowband two-phase Chan-Vese(ANBCV) model is proposed for im?proving the shadow regions detection performance of sonar images. In the first noise smoothing step, the anisotropic second-order neighborhood MRF(Markov Random Field, MRF) is used to describe the image texture feature parameters. Then, initial two-class segmentation is processed with the block mode /c-means clustering algorithm, to estimate the approximate position of the shadow regions. On this basis, the zero level set function is adaptively initialized by the approximate position of shadow regions. ANBCV model is provided to complete local op?timization for eliminating the image global interference and obtaining more accurate results.Experimental results show that the new algorithm can efficiently remove partial noise, increase detection speed and accuracy, and with less human intervention.     

一种实时检测遮挡阴影的算法

监控系统中,观测视场被遮挡,会导致显示的图像中存在遮挡阴影,影响对图像的进一步分析和处理.针对该问题,提出了一种实时检测遮挡阴影的算法.该算法基于图像序列的帧间运动特性对图像进行分区处理;利用图像子区域的灰度均值进行帧间预测,用来判断图像序列中被遮挡图像帧和可能的遮挡阴影区域;利用空域滤波器剔除误检区域,确定阴影区域.该算法实时性好,易于工程实现.     

Narrowband Chan-Vese model of sonar image segmentation: A adaptive ladder initialization approach

A narrowband Chan-Vese model with adaptive ladder initialization approach is proposed in this paper to segment underwater sonar image. Specifically, for the first time, the problem of more iterative times, human intervention necessity and lower segmentation accuracy, which are commonly exist in the SDF and BIF, was solved with the method utilizing the new adaptive ladder initialization of zero level set. Then, to further reduce the impact of the global search on traditional Chan-Vese model, the narrowband Chan-Vese model is introduced. It is shown that by applying the adaptive ladder initialization is ultimately local optimization and accurate segmentation results. On this basis, recurring to analysis of traditional Chan-Vese model law, combined with narrowband Chan-Vese model with adaptive ladder initialization approach, the objective and quantitative analysis method is developed. Finally, segmentation results demonstrate the effectiveness and adaptability of the proposed method.     

Binaural detection with narrowband and wideband reproducible noise maskers. III. Monaural and diotic detection and model results

A single-interval, yes-no, tone-in-noise detection experiment was conducted to measure the proportion of "tone present" responses to each of 25 reproducible noise-alone and tone-plus-noise waveforms under narrowband (100 Hz), wideband (2900 Hz), monotic, and diotic stimulus conditions. Proportions of "tone present" responses (estimates of the probabilities of hits and false alarms) were correlated across masker bandwidths and across monotic and diotic conditions. Two categories of models were considered; one based on stimulus energy or neural counts, and another based on temporal structure of the stimulus envelope or neural patterns. Both categories gave significant correlation between decision variables and data. A model based on a weighted combination of energy in multiple critical bands performed best, predicting up to 90% of the variance in the reproducible-noise data. However, since energy-based models are unable to successfully explain detection under a roving-level paradigm without substantial modification, it is argued that other variations of detection models must be considered for future study. Temporal models are resistant to changes in threshold under roving-level conditions, but explained at most only 67% of the variance in the reproducible-noise data.     

自适应多方向灰度形态学图像边缘检测算法

针对传统的多方向灰度形态学边缘检测算法存在计算量大、效率低的缺点,提出了一种基于自适应噪声抑制的多方向灰度形态学图像边缘检测算法。根据图像所含噪声的种类,采用不同尺度的结构元素对图像进行分类滤波,再根据像素点间灰度值的变化确定边缘方向,由相应方向的结构元素进行边缘检测。实验结果表明,与传统的多方向灰度形态学边缘检测算法相比,检测到的边缘重构相似度和边缘置信度更高,边缘连续性更强,且计算量低,运行效率高。     

水下网络突发分组前导码检测的自适应阈值算法

本文针对水声信道的特点,提出了一种适于水下传感器网络突发通信分组前导码检测的自适应阈值算法。该算法根据估计的信号瞬时功率自适应地调整阈值,以取代固定阈值算法中的预设常数阈值。进行了理论分析和仿真,证明该算法具有恒虚警的特点,检测概率比固定阈值算法有明显的提高。针对检测到相关函数旁瓣的情况,加入了滑动窗口。该算法经过了湖试验证,性能良好,具有实用价值。     

基于自适应非参数统计模型的彩色目标跟踪算法研究

针对复杂环境条件下的视觉跟踪问题,提出一种基于自适应非参数统计模型的彩色目标跟踪算法。利用目标和背景之间的强度差别,基于自适应核密度估计模型对运动目标进行了非参数统计建模。为了实现具有较大范围运动目标的跟踪,在充分考虑目标和背景之间的相关性前提下,采用目标特征统计的背景加权直方图对搜索区域进行了扩大。为了提高对环境变化的适应能力,根据目标和环境的变化自适应更新目标特征分布模型。通过对实际图像序列的实验,结果表明该算法能够有效跟踪运动目标,并且平均迭代次数比传统方法减少了37.28%。     

基于双路多尺度金字塔池化模型的显著目标检测算法

为提升复杂环境装甲目标的检测精度,提出了一种显著目标检测算法,该算法通过视觉注意机制与联合金字塔上采样模块分别获取视觉注意机制约束的低层次特征与多尺度池化语义特征,利用聚合策略进行融合,提升低对比度或遮挡情况下的目标表征能力。测试结果表明,文中算法对复杂场景下多尺度目标均取得了良好的检测效果,其精度、召回率与平均精度分别为72.2%、71.4%与77.1%,能够满足实际应用需求。     

Circular antenna design by adaptive position inheritance artificial bee colony algorithm

Reliable communication is a key factor in the development of the fifth generation wireless communication systems. To achieve reliable communication, designing desirable antenna arrays is the basis so as to realize wireless data transmission. Artificial bee colony (ABC) algorithm has shown its powerfulness in engineering design problems, though the performance of ABC could be improved further through information exchange of existing solutions. This paper proposes an adaptive position inheritance strategy for ABC algorithm. It adaptively decides the number of positions to be inherited attached with the evolutionary process of the algorithm. Take circular antenna as design example. The proposed algorithm is tested against with method of exhaustion. Simulation results show the usefulness of the proposed algorithm. Moreover, the proposed algorithm is also compared with state of the art algorithm under ABC paradigm. It turns out that the proposed algorithm attains better design solution. Thus, the proposed algorithm is useful for providing good design solutions in reliable communication.