Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).     

小波变换在光谱特征提取方面的应用

人们在处理高光谱图像时一般要对一些典型地物进行光谱分析、特征波段的提取,以便提取出最大量的有效信息,剔除无用或冗余的信息,然后再进行分类识别.采用小波变换的分析方法,选用合适的小波进行分解,根据分解后的高频分量中包含的重要信息,利用局部相邻的正负极值点找出对应于原始光谱曲线上每个吸收带的左右边界;利用局部过零点,即可比较精确的提取出各个吸收带的中心波长.该方法比传统的光谱特征提取方法更简洁、有效,实验证明为一种比较理想的光谱特征提取方法.     

微波陶瓷基印制板制造工艺性研究

对微波陶瓷基印制板的制造工艺流程进行了简单的介绍,对所采用的工艺技术的有效性进行了较为详细的论述。     

高分辨率地震资料处理中的优化速度分析方法

速度分析是地震资料处理过程中的重要一环。速度分析的质量直接影响动静校正,继而影响叠加成像以及偏移归位。针对如何优化速度分析,提出了基于道集资料噪音衰减、道集内相位时差校正、道集优化处理以及速度拾取应用约束等过程的优化速度分析方法。该方法在实际资料处理中取得了很好的效果。     

Quality Control for Scalable Media Processing Applications

Many media processing applications create a load that varies significantly over time. Hence, if such an application is assigned a lower processing-time budget than needed in its worst-case load situation, deadline misses are likely to occur. This problem can be dealt with by designing media processing applications in a scalable fashion. A scalable media processing application can run in multiple qualities, leading to correspondingly different resource demands. The problem we consider is to find an accompanying quality control strategy, which minimizes both the number of deadline misses and the number of quality changes, while maximizing the quality of processing. We present an initial approach to the above problem by modeling it as a Markov decision process (MDP). Our model is based on measuring relative progress at milestones. Solving the MDP results in a quality control strategy that can be applied during runtime with only little overhead. We evaluate our approach by means of a practical example, which concerns a scalable MPEG-2 decoder.     

对基于交换网络分层结构的软件无线电方案的改进

通过比较各种软件无线电结构的优缺点,针对既具有交换网络结构又具有分层结构优点的基于交换网络的分层无线电结构方案,提出了部分改进思想。     

空间数据立方体的物化视图选择方法研究

针对决策支持系统(DSS)中集成空间分析能力的应用趋势，研究基于空间数据仓库的一种决策分析工具——空间在线分析处理(Spatial OLAP)，拟解决影响空间OLAP在线响应的瓶颈难点——空间数据立方体的物化问题。首先系统地提出空间OLAP的模型，然后对现有空间度量物化视图选择方法进行改进，提出了双向空间Greedy算法。实验证明．该算法在降低选择时间和求解质量两方面具有更好的表现。     

工业管道测厚的几点问题探讨

超声波测厚在腐蚀监测上应用越来越广泛,为让这项检测技术更准确、更可靠,充分发挥功效,文章就工业管道测厚中测厚数据处理、测厚点选择、高温问题以及其它影响因素等几个方面进行了探讨。     

小波变换分离太阳射电频谱图中的纤维结构

太阳射电爆发纤维精细结构是太阳射电爆发活动中一类重要的观测现象,利用二维小波变换对纤维精细结构动态频谱图进行处理,分离频谱图中的纤维结构。首先对原始频谱图实行多层小波变换,由低频分量重构原始图像,就可得到爆发的背景信息,令原始频谱图减去背景并经过阈值处理后,便可将原始频谱图中的纤维结构很好地分离出来。     

加快塑料技术中心建设提高新产品开发水平

对中国石油化工集团公司(简称中国石化)合成树脂生产及加工应用技术的现状进行了分析，指出中国石化应加快建设塑料加工应用技术中心，为塑料产品的加工用户提供高技术水平和快捷周到的技术服务，在合成树脂新产品开发和产品结构调整中发挥积极作用，以提高合成树脂产品的市场竞争力。