关于融合多针图确定表面绝对深度的误差分析与研究

本文利用ＢＰＳ系统首先产生景物的一对表面方向图，然后：１．分割表面方向图为与景物内物体对应的孤立区域；２．匹配两针图内对应区域间的视差；３．确定物体的３Ｄ表面绝对深度，最后，着重指出怎样识别以下几种主要误差：（１）表面方向测量误差；（２）重建深度误差；（３）极线与扫描线非平行误差等，并且讨论对这些误差进行定量分析与校正的方法。     

多物体3D显示的双屏幕技术

本文提出了一种快速实现二维断层图象序列中多物体三维显示的双屏幕技术。将此技术应用于医学ＣＴ断层图象中肝脏，肿瘤和血管多物体的３Ｄ重建显示。结果令人满意。     

基于矩的异分辨率图象边界检测

（１）本文引入仿射变换，提出了一种用矩算子以民分辨率图象直接进行边界检测的方法，利用同分辨率图象正方形窗口的模板行矩的计算，推导出了相应用的边界参数公式。（２）本文提出一种隐线笥插值矩计算方法，得到一组与正方形窗口对应的正方形模板，避免了费时的预插值过程，（３）对本文提出的方法进行了实验验证，并给出了实验结果。     

清晰热成象红外双色肖特基势垒CCD图象传感器

用控制肖特基光电二极管阵列势垒高度的方法，研制出象素包含低和高势垒高度二极管的红外双色肖特基ＣＣＤ图象传感器。研制的６４８（Ｈ）×４８８（Ｖ）红外双色ＣＣＤ图象传感器转移效率高达９９．７４％，解决了常规单色红外ＣＣＤ图象传感器探测灰色物体温度的错误，获得清晰的热成象。     

CCD相机广角镜头的光学系统设计

由于ＣＣＤ（电荷耦合器件）可作为光学系统的接受器，构成光电光学系统，既可实现光电能量转换，又可进行光电图象转换，所以得到广泛的应用，随之对光学系统提出新的要求．本文对ＣＣＤ相机广角镜头的光学系统设计方法进行了研究，并给出视场角为１００°，ＣＣＤ靶面分别为１／２英寸和１／３英寸的光学系统设计方法和设计结果。     

用于D－3格式录像机的一种新型8－14信道编码方式

新型８－１４信道编码技术适合于数字录像机高密度记录。该编码将８比特数据变换为１４比特的记录数据，且ＤＳＶ（数据总和变化）最大绝对值为７，最小记录波长比Ｓ－ＮＲＺ（ＳｃｒａｍｂｌｅＮＲＺ码，Ｄ－１录像机采用）和Ｍ２（Ｍｉｌｌｅｒ２码，Ｄ－２录像机采用）编码长１４％，记录带宽窄１２．５％。其优点是：简化了记录，重放均衡，采用方位角记录，对误码检测无误差传播。测试结果表明；重放信号比Ｓ－ＮＲＺ和Ｍ２的Ｓ／Ｎ（信噪比）高２．８ｄＢ。目前，Ｄ－３格式ＶＴＲ中已采用了８－１４信道编码方式。     

多电平变换器——功率变换器新品种

多电平变换器是大功率应用优选功率变换器新品种时才引人注目的，本文阐述最新发展的三种多电平变换：（１）二极管箝位；（２）浮动电容器；（３）有各自直流源的级联逆变器，经计算机仿真，并用ＩＧＢＴ作功率开关器件和ＤＳＰ作全数字控制器的样机验证，给出了工作原理、特点，优缺点和应用范围。     

基于Bayes决策的组合中值滤波

针对图象滤波中的滤噪和细节保护的矛盾，提出了基于Ｂａｙｅｓ决策的组合中值滤波技术，内容有：（１）导出了测试向量的联合分布密度函数；（２）提出了先验概率的一种估计算法，该算法有一定的普遍应用意义；（３）基于Ｂａｙｅｓ决策，将标准中值滤波器（ＭＦ）和多级中值滤波器（ＭＬＭ）组合应用，给出一种效果优良的组合中值滤波器结构。     

数字Hilbert变换器与Hilbert变换器的关系

本文讨论数字Ｈｉｌｂｅｒｔ变换器（ＤＨＴ）与Ｈｉｌｂｅｒｔ变换器（ＨＴ）间的关系，取得下列结果：（１）ＤＨＴ变换是ＨＴ变换的数字仿真器；（２）ＨＴ变换可由ＤＨＴ变换来实现；（３）数字实信号的复信号可由连续时间实信号的复信号取样得到。     

红宝石激光晶体零场分裂及其光谱精细结构研究

推导了ｄ＾３（Ｃ＾＊３ｖ）组态离子的中间场能量矩阵，建立了红宝石（Ｃｒ＾３＋：Ａｌ２Ｏ３）晶体基态＾４Ａ２零场分裂（ＺＦＳ）参量Ｄ及＾２Ｅ态分裂△Ｅ（＾２Ｅ）与晶体结构之间的定量关系；假设晶格畸变的基础上，统一地计算了Ｃｒ＾３＋：Ａｌ２Ｏ３晶体的ＺＦＳ参量Ｄ、Ｚｅｅｍａｎｇ因子、精细光谱及＾２Ｅ态的分裂△Ｅ（＾２Ｅ），计算结果与实验观测十分吻合，定量的研究结果表明：当Ｃｒ＾３＋离子掺入Ａｌ２Ｏ３晶     

Using multi-modal 3D contours and their relations for vision and robotics

In this work, we make use of 3D contours and relations between them (namely, coplanarity, cocolority, distance and angle) for four different applications in the area of computer vision and vision-based robotics. Our multi-modal contour representation covers both geometric and appearance information. We show the potential of reasoning with global entities in the context of visual scene analysis for driver assistance, depth prediction, robotic grasping and grasp learning. We argue that, such 3D global reasoning processes complement widely-used 2D local approaches such as bag-of-features since 3D relations are invariant under camera transformations and 3D information can be directly linked to actions. We therefore stress the necessity of including both global and local features with different spatial dimensions within a representation. We also discuss the importance of an efficient use of the uncertainty associated with the features, relations, and their applicability in a given context.     

Interpretation of Multisensor Remote Sensing Images: Multiapproach Fusion of Uncertain Information

Land cover interpretation using multisensor remote sensing images is an important task that allows the extraction of information that is useful for several applications. However, satellite images are usually characterized by several types of imperfection, such as uncertainty, imprecision, and ignorance. Using additional sensors can help improve the image interpretation process and decrease the associated imperfections. Fusion methods such as the probability, possibility, and evidence methods can be used to combine information coming from these sensors. An extensive literature has accumulated during the last decade to resolve the issue of choosing the best fusion method, particularly for satellite images. In this paper, we present a semiautomatic approach based on case-based reasoning (CBR) and rule-based reasoning, allowing intelligent fusion method retrieval. This approach takes into account the advantage of data stored in the case base, allowing a more efficient processing and a decrease in image imperfections. The proposed approach incorporates three modules. The first is a learning module based on evaluating three fusion methods (probability, possibility, and evidence) applied to the given satellite images. The second looks for the best fusion method using CBR. The last is devoted to the fusion of multisensor images using the method retrieved by CBR. We validate our approach on a set of optical images coming from the Satellite Pour l'Observation de la Terre 4 and radar images coming from European Remote Sensing Satellite 2 (ERS-2) representing a central Tunisian region.      

R&D/marketing communication during the fuzzy front-end

The planning stage of an innovation project has a great effect on the commercial performance of the project. During the “fuzzy front-end”, the organization formulates a concept of the product to be developed, and determines whether or not the organization will invest resources in the concrete development of the idea. The integration of R&D and marketing activities is a necessary condition for success in innovation projects. The research question of this study is: from an information processing perspective, what role does information transfer play in integrating R&D and marketing functions during the planning stage, and what effects do project formalization and project centralization of R&D and marketing planning activities have on the efficiency of marketing and technological uncertainty reduction? The authors use an ex post facto research design to test the propositional model. The findings show that successful project teams are characterized by a maximum uncertainty reduction during planning, i.e., by a maximum decrease of R&D and marketing task variability, and a maximum increase of R&D and marketing task analyzability. Information flows between these functions help them to achieve this efficient uncertainty reduction. While project centralization has a negative effect on efficient uncertainty reduction, project formalization is curvilinearly related to the amount of uncertainty reduced during planning     

基于不完美CSI的D2D通信网络鲁棒能效资源分配算法

针对设备到设备(D2D)直连通信网络传统最优资源分配算法在随机信道时延、信道估计误差影响下鲁棒性弱的问题,该文在考虑参数不确定性影响的条件下,提出D2D用户总能效最大的鲁棒资源分配算法。考虑干扰功率门限、用户最小速率需求、最大传输功率和子信道分配约束,建立了下垫式频谱共享模式下多用户D2D网络资源分配模型。基于有界信道不确定性模型,利用最坏准则方法将原非凸鲁棒资源分配问题转换为确定性的凸优化问题。然后利用拉格朗日对偶理论求得资源分配的解析解。仿真结果表明所提出的算法具有很好的鲁棒性。     

基于可信度区间的不确定性推理

不确定性推理一直是人工智能研究的重点,基于此首先阐述了不确定性推理规则的组成及其含义,然后提出了不确定性推理的通用模型,给出了一种基于可信度区间的推理方法,通过引入可信度区间、区间匹配函数来进行不确定性推理,在推理结果中通过引入权重系数来进行区间排序,从而衡量各个结果,使得推理结果更加接近实际情况。通过实例算法验证,该方法简单有效。     

3D Deformable Convolution Temporal Reasoning network for action recognition

Modeling and reasoning of the interactions between multiple entities (actors and objects) are beneficial for the action recognition task. In this paper, we propose a 3D Deformable Convolution Temporal Reasoning (DCTR) network to model and reason about the latent relationship dependencies between different entities in videos. The proposed DCTR network consists of a spatial modeling module and a temporal reasoning module. The spatial modeling module uses 3D deformable convolution to capture relationship dependencies between different entities in the same frame, while the temporal reasoning module uses Conv-LSTM to reason about the changes of multiple entity relationship dependencies in the temporal dimension. Experiments on the Moments-in-Time dataset, UCF101 dataset and HMDB51 dataset demonstrate that the proposed method outperforms several state-of-the-art methods.     

Programmed Shape‐Morphing Scaffolds Enabling Facile 3D Endothelialization

Rapid formation of a confluent endothelial monolayer is the key to the success of small‐diameter vascular grafts, which is significantly important for treating dangerous and even sometimes deadly vascular disorders. However, the difficulty to homogenously locate endothelial cells onto the lumen of small‐diameter tubular scaffolds makes 3D endothelialization greatly challenging. Here, novel shape‐morphing scaffolds enabling programmed deformation from planar shapes to small‐diameter tubular shapes are designed and developed by combining biocompatible shape memory polymer and electrospun nanofibrous membrane. Endothelial cells can be conveniently seeded and attached on the 2D surface of the scaffolds and subsequently self‐rolled into 3D organization at physiological temperature. Endothelial cell responses and functions are varied on the shape‐morphing scaffolds with different nanofibrous electrospun membranes as the inner layer, arisen from the inducement of scaffolds with different morphological, physical, and biochemical characteristics. Owing to excellent properties of the nanofibrous membrane fabricated by the coelectrospinning of poly‐ε‐caprolactone (PCL) and gelatin methacrylate (GelMA), the shape‐morphing scaffolds with a nanofibrous PCL/GelMA inner layer support desirable homogeneous endothelial cell attachment as well as the rapid formation of biomimetic cell–scaffold interaction and cell–cell interaction under the 3D cell culture condition, therefore offering a visible approach for facile 3D endothelialization.     

A distributed approach to 3D road scene recognition

A distributed 3D scene recognition system based on a multilevel representation of object models and signals is described. The solution to a recognition problem is obtained through a set of object-observation couples at the different abstraction levels. The various system modules exchange two kinds of information: (1) top-down messages, which are used to communicate to lower modules the predictions made on the basis of a priori knowledge on the application domain, (2) bottom-up messages, which are used to communicate to higher modules the evidence supporting possible local solutions. A local scheme for the combination of message flows is defined, and messages are interpreted by using a probabilistic network of estimators of random variables. The proposed model is suitable for addressing the problem of distributed geometric reasoning aimed at 3D road scene recognition by an autonomous vehicle. Recognition results include road detection and obstacle localization, together with a study of the relative computational load required by different modules of the system. The proposed approach is currently simulated on a workstation, while an effective implementation on board of an autonomous vehicle is under development in the contest of the CEC-EUREKA Prometheus project     

3D tetrahedron ray tracing algorithm

A new three-dimensional (3D) tetrahedron meshed ray tracing (TMRT) method is proposed. It is based on dividing the propagation region into tetrahedral cells whereby the number of tetrahedrons is decided by the number of vertices of structures instead of their dimensions. This method represents a 3D extension to the 2D procedure described in an earlier paper. Results from the 3D TMRT method show significant improvement in computational efficiency and are typically less than one half of those of the visibility ray tracing approach. These results were illustrated by calculating the delay spread in a typical indoor propagation environment     

Display of 3D information in discrete 3D scenes produced by computerized tomography

Imaging modalities such as X-ray computerized tomography (CT), ultrasound CT, and nuclear magnetic resonance CT all produce sequences of slice images of internal structures of medical objects. Effective methods of displaying the 3D information in such images are essential to aid in both diagnosis and treatment of diseases. Two philosophically different approaches to the display problem have been pursued. In the first approach, 3D information is displayed as a distribution of densities in a 3D space. The second approach extracts, from slice images, information about boundary surfaces of objects which is displayed on a 2D screen. The present paper reviews both of these approaches with particular emphasis on the image and graphics processing aspects of the latter approach.