Skeleton pruning as trade-off between skeleton simplicity and reconstruction error

The position and orientation of moving platform mainly depends on global positioning system and inertial navigation system in the field of low-altitude surveying, mapping and remote sensing and land-based mobile mapping system. However, GPS signal is unavailable in the application of deep space exploration and indoor robot control. In such circumstances, image-based methods are very important for self-position and orientation of moving platform. Therefore, this paper firstly introduces state of the art development of the image-based self-position and orientation method (ISPOM) for moving platform from the following aspects: 1) A comparison among major image-based methods (i.e., visual odometry, structure from motion, simultaneous localization and mapping) for position and orientation; 2) types of moving platform; 3) integration schemes of image sensor with other sensors; 4) calculation methodology and quantity of image sensors. Then, the paper proposes a new scheme of ISPOM for mobile robot — depending merely on image sensors. It takes the advantages of both monocular vision and stereo vision, and estimates the relative position and orientation of moving platform with high precision and high frequency. In a word, ISPOM will gradually speed from research to application, as well as play a vital role in deep space exploration and indoor robot control.     

Compressed sensing of superimposed chirps with adaptive dictionary refinement

The compressed sensing （CS） theory shows that accurate signal reconstruction depends on presetting an appropriate signal sparsifying dictionary. For CS of superimposed chirps, this dictionary is typically taken to be a waveform-matched dictionary formed by blindly diseretizing the frequency-chirp rate plane. However, since practical target parameters do not lie exactly on gridding points of the assumed dictionary, there is always mismatch between the assumed and the actual sparsifying dictionaries, which will cause the performance of conventional CS reconstruction methods to degrade considerably. To address this, we model the waveform- matched sparsifying dictionary as a parameterized one by treating its sampled frequency-chirp rate grid points as the underlying parameters. As a consequence, the sparsifying dictionary becomes refinable and its refinement can be achieved by optimizing the underlying parameters. Based on this, we develop a novel reconstruction algorithm for CS of superimposed chirps by utilizing the variational expectation-maximization （EM） algorithm. By alternating between steps of sparse coefficients estimation and dictionary parameters optimization, the algorithm integrates the process for dictionary refinement into that of signal reconstruction, and thus can achieve sparse reconstruction and dictionary optimization simultaneously. Experimental results demonstrate that the algorithm effectively deals with the performance degradation incurred by dictionary mismatch, and also outperforms the state-of-the-art CS reconstruction methods both in compressing the signal measurements and in suppressing the measurement noise.     

用圆锥体拟合线性模型点云数据的优化计算

针对采用最小圆锥形(包括圆柱、圆锥和圆台)拟合任意轴向的线性模型的点云数据这个NP-难问题,提出一种优化算法.该算法将具有n个点的点云模型自适应地分解成一些子集,并对每个子集用一个圆锥来拟合,使得圆锥包含对应子集内所有点,且拟合圆锥的体积小于最优解的(1+ε)倍.其中圆锥拟合方法的时间复杂度为O(n/ε3),ε是用户给定的拟合误差,优于已有最快拟合方法的复杂度.实验结果表明文中算法是快速有效的.     

标记监补模式下的网站监视反病毒系统

根据现有杀毒软件的局限性,针对网站安全提出并开发了一套完善网站安全系统.它根据独有的标记监补模式,准确定位被感染的文件、被修改的文件、木马文件等.根据每个网页文件的不同特点计算出不同的特征字符,存放于每个网页中,在后期维护中,根据每个网页文件的特点再次计算出特征字符,并搜索预先存放于网页的特征字符,通过比较可以准确定位...     

三菱“GX-8100家族系列”——全面给力高端工程投影市场

近两年,工程投影机市场销量每年都有一倍以上的增长,工程投影市场已经成为行业中增长最快的领域。工程投影机在机场、商业广场等大型户外广告;煤炭、水力等工程的监控系统;大型的礼堂、议会厅等环境中都得到了广泛的应用。另外,2010年的上海世博会和广州亚运会接连召开,让高端工程投影机更多新的应用模式被发掘出来,更多应用需求被激发出来。加上这类高技术、高门槛的产品利润率相对较高,高端投影机将成为继教育投影机之后,另一个投影行业的竞争热点。     

高分辨率SAR图像建筑物三维成像几何结构分析

随着SAR分辨率的不断提高,建筑物在SAR图像上表现出越来越明显的几何结构特征,这些特征为重建建筑物三维模型提供了重要的信息。主要论述了建筑物在SAR图像上的成像几何结构,并给出了利用SAR图像上建筑物L型的叠掩结构反演建筑物三维结构的理论基础和方法,最后通过实验证明了该方法的可行性。     

电容层析成像技术的近期研究进展

详细介绍了电容层析成像技术(ECT)的近期研究进展.在简要介绍电容层析成像系统的基础上,重点总结了电容层析成像技术应用研究现状.包括图像重建算法、实验室应用、硬件系统设计和现场应用等方面的研究.最后指出电容层析成像技术发展中亟待解决的问题,为研究该领域指明了努力的方向.     

一种空间自适应正则化MAP超分辨率重建算法

提出一种简单、通用的基于正则化技术的自适应MAP超分辨率重建算法。与以往算法不同,该方法引入了局部空间自适应正则化参数,弥补了传统算法对图像自身的局部特性缺乏考虑的不足。算法通过迭代的方式,利用中间重建结果不断对正则化参数进行更新,并最终得到重建图像。实验结果表明,该方法可以根据不同图像序列的特点以及图像的局部灰度特性,自适应地确定相应的正则化参数,并找到最优解,有效地保护了高分辨率图像的细节信息。     

模拟退火遗传算法的轮廓线拼接研究

基于断层数据的三维重构是三维数据场可视化技术的主要研究内容,重构物体的三维模型也是分析、仿真的前提.应用模拟退火遗传算法设计和实现了三维物体表面重建算法.通过在遗传算法中融人退火处理操作,提高了种群的多样性,避免了遗传算法中存在的早熟收敛问题,有效地增强了算法的全局寻优能力.此外,提出了一种基于边的最小交叉多边形算法,提高了交叉操作效率.根据轮廓线拼接问题的特点,设计了针对性强的交叉、变异操作.实验结果表明,算法有效地提高了传统的全局法轮廓线拼接算法的效率.     

空间自适应正则化超分辨率图像重建

超分辨率图像重建是一个病态问题,在重建过程中需要正则化处理,而正则化重建会引入正则化误差及重建过程中由于病态性而引入的噪声放大误差,且这两类误差均和图像的空间局部特性有关.提出根据图像的局部空间统计特性自适应控制超分辨率图像正则化重建算法,采用图像局部统计方差来区分图像棱边区域及平滑区域,在图像的棱边区域加强图像的约束重建,而在图像的平滑区域加强正则化.实验表明该算法能有效地减小重建误差,算法的信噪比得益优于传统的正则化重建算法及总变分模型重建算法,并且对正则化参数的选择具有一定的鲁棒性.