Mutual information based registration of multimodal stereo videos for person tracking

Research presented in this paper deals with the systematic examination, development, and evaluation of a novel multimodal registration approach that can perform accurately and robustly for relatively close range surveillance applications. An analysis of multimodal image registration gives insight into the limitations of assumptions made in current approaches and motivates the methodology of the developed algorithm. Using calibrated stereo imagery, we employ maximization of mutual information in sliding correspondence windows that inform a disparity voting algorithm to demonstrate successful registration of objects in color and thermal imagery. Extensive evaluation of scenes with multiple objects at different depths and levels of occlusion shows high rates of successful registration. Ground truth experiments demonstrate the utility of the disparity voting techniques for multimodal registration by yielding qualitative and quantitative results that outperform approaches that do not consider occlusions. A basic framework for multimodal stereo tracking is investigated and promising experimental studies show the viability of using registration disparity estimates as a tracking feature.     

黑板型信息融合专家系统在水环境监测中的应用

现代水环境监测系统是一个具有现代高性能、多层次的复杂系统,这要求多个(种、异质)传感器在不同尺度上对水环境进行观测。探讨和分析了信息融合技术应用于水环境监测的特点,提出了一种运用专家系统和黑板理论的水环境监测信息融合结构框架。     

Concealed weapon detection and visualization in a synthesized image

Images acquired by heterogeneous image sensors may provide complementary information about the scene, for instance, the visual image can provide personal identification information like the facial pattern while the infrared (IR) or millimeter wave image can detect the suspicious regions of concealed weapons. Usually, a technique, namely multiresolution pixel-level image fusion is applied to integrate the information from multi-sensor images. However, when the images are significantly different, the performance of the multiresolution fusion algorithms is not always satisfactory. In this study, a new strategy consisting of two steps is proposed. The first step is to use an unsupervised fuzzy k-means clustering to detect the concealed weapon from the IR image. The detected region is embedded in the visual image in the second step and this process is implemented with a multiresolution mosaic technique. Therefore, the synthesized image retains the quality comparable to the visual image while the region of the concealed weapon is highlighted and enhanced. The experimental results indicate the efficiency of the proposed approach.This material is based on part of the work carried out at the SPCR laboratory of Lehigh University and the work is partially supported by the U. S. Army Research Office under grant number DAAD19-00-1-0431. The content of the information does not necessarily reflect the position or the policy of the federal government, and no official endorsement should be inferred.     

基于分形方法的机载雷达云仿真

为了提高军事仿真训练的逼真程度,根据云的特性以及机载气象雷达上云的成像,提出了一种虚拟云的建模方法,应用分形技术中一种改进的逐次随机增加法进行云数据建模,并且选择适当的控制源曲面,在此控制源曲面基础上与分形生成的曲面进行加权融合,生成具有预定形状的云数据模型。最后将此数据模型按照一定的生成法则在相应点映射成颜色值,建立高度和颜色值的对应关系,可实现机载气象雷达屏幕云的成像仿真。     

火星探测器转移轨道的自主导航方法

本文针对转移轨道火星探测器对自主导航的迫切需求,提出了一种基于小行星和X射线脉冲星交互观测的自主导航方法,并结合工程任务对上述量测信息的获取方式和获取条件进行了研究,仿真结果表明,与单独基于小行星或单独基于X射线脉冲星观测的自主导航系统相比,该方法不仅可获得更高的导航精度,为转移轨道中途修正提供准确的轨道信息,且工程实现简单,是一种可行的转移轨道火星探测器自主导航方案,可为我国火星探测器自主导航系统的设计提供参考.     

融合网络宽带互动电视系统设计

文章对融合网络宽带互动电视系统进行了简要的介绍,从系统设计方案、系统设计特点以及系统的结构设计等方面对技术方案进行分析。     

多特征自适应融合的粒子滤波跟踪算法

针对跟踪过程中目标形态不断变化或部分遮挡导致鲁棒性差的问题,提出一种基于多特征自适应融合的粒子滤波跟踪算法.该算法从视觉特征集中选取了描述能力强的2种特征,并将其按照与目标模型的多尺度相似度进行线性融合;为了减小跟踪漂移,通过计算当前目标模型与初始目标模型的多尺度相似度自适应地更新目标模型.大量仿真实验结果表明,文中算法可以鲁棒地跟踪到部分遮挡和形态变化的运动目标.     

异类传感器实时信息融合的STMHM算法

异类传感器实时信息融合由于两类设备的数据率不同和数据误差的限制,一直未得到有效解决,提出一种空时二维多假设模型(STMHM)算法来解决该问题。设计的融合数据模型,将异类传感器的测量数据映射在二维直角坐标系下;按照新的融合数据模型分别构建两类传感器的目标量测空间和融合空间;设计量测空间时间初始化方法和目标实体空间的滤波算法;通过仿真验证表明:该算法能够实现异类传感器的信息融合,初次融合成功的确认时间在3～5个主动传感器扫描周期。     

一种基于区域分割的多尺度遥感图像融合方法

光谱保持和高分辨率保留是图像融合的重要问题,提出了一种区域分割和小波变换相结合的多尺度遥感图像融合方法。首先对经过配准的待融合图像进行小波变换,然后对变换后的低频系数进行基于区域标准差的分割,将低频系数分为目标信息和背景信息,接着对目标信息采取基于绝对值的融合,对背景信息采用基于灰度误差的融合。对小波变换后的高频系数采用基于清晰度的融合规则,最后进行小波逆变换得到融合图像。将该方法和几种常用融合方法进行对比分析,结果表明:该方法在有效地保持多光谱影像光谱信息的同时,可以有效地提高融合影像的空间细节信息,有利于后续进行信息提取和图像分类。