结合位图切割和区域合并的彩色图像分割

就经典分水岭图像分割算法中存在的过分割问题，提出一种结合位图切割和区域合并的彩色图像分割算法。对原始彩色图像通过空域梯度算子求其梯度图像，并利用位图切割重建梯度图像；对新梯度图像进行分水岭预分割；对预分割图像基于异质性最小原则进行区域合并，并获得最终分割结果。相比于现有的同类方法，该算法引入位图切割，抑制噪声对分割结果的影响，在边缘模糊处分割准确，得到符合人类视觉的较小分割区域数目，同时在运行效率上提高。     

基于宏观经济结构合理化的宁夏水资源合理配置

本文分析了宁夏目前经济结构下水资源利用效率及产出效益，研究在一定经济发展水平下，当资源配置最优时，最优的经济均衡增长途径。区域最优经济结构是由国民经济各部门相互依存的关联关系技术矩阵所决定的，其均衡增长率和均衡增长产出结构分别等于非负矩阵的弗罗比尼斯特征根和相对应的弗罗比尼斯向量。本文根据联合国经济发展统计数据，分析出宁夏未来调整第一产业与第二产业结构的比例，认为应适当减少宁夏高耗水水稻种植面积，逐渐把农业用水量向工业用水量转移。转变经济增长方式，从水资源的高效利用及配置出发走内涵式、节水型的社会发展道路，以解决宁夏水资源严重不足的问题。     

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).     

合成氨制气中的以水代汽新工艺

提出了应用油水融合技术在合成氨部分氧化法制气中以水代汽的工艺途径，并分析了其效果和意义。     

HIS变换用于数字化航空片影象同多光谱影象的复合

本文探讨ＨＩＳ变换对数字化航空片影象与ｌａｎｄｓａｔ ＴＭ多光谱影象进行复合的方法，并在此基础上提出一种改进的方法。试验结果表明本文提出的方法是一种非常行之有效的方法。复合后的影象不仅保留了ＴＭ影像的光谱特征，而且将其空间分解力由３０ｍ提高到１０ｍ，清晰度也提高了。因而复合后的影像能提高分类精度，制作专题图的精度、多时相监测能力和解译水平等。     

基于区域生长法的医学图像分割研究

针对基于区域的分水岭分割算法中通常存在的严重过分割现象，通过两点措施来改进：其一，以梯度图像的浮点活动图像取代梯度图像进行分水岭变换，使边缘定位更准确；其二，以基于面积和对比度控制的合并小区域准则，有效抑制过分割现象，同时满足感兴趣区的分割要求。实验表明该算法简单有效，能够得到符合人类视觉系统特性的分割结果，边缘定位精确度较高。     

RLL码的计算机辅助设计

本文着重讨论计算机辅助设计RLL码的具体实现问题.该过程首先根据RLL码两个参数d,k确定一个编码率p/q,然后构造出RLL码的高阶状态转换-输出符号矩阵并求相应的近似特征向量.最后通过状态分裂和状态归并过程,即可得到一个满足d,k约束的编码输出表.其中状态转换-输出符号矩阵为实现计算机辅助设计RLL码提供了有效的数据结构,而且要优化RLL码编码器,就必须有选择地进行状态分裂.     

五号桩—长堤地区沙河街组砂体储集性及控制因素研究

沙河街组是沾化凹陷东部五号桩-长堤地区重要的储油层系，主要目的层段为沙三段和沙二段。沙三段和沙二段主要发育有浊积扇、水下冲积扇和滩坝沉积体系，在浊积扇、水下冲积扇中发育辫状水道、扇中前缘、辫状水道间以及扇根、扇缘等沉积微相类型，其中辫状水道、扇中前缘砂体物性好，原生孔隙及次生孔隙均较发育，辫状水道间以及扇根砂体物性较差。其储集特征主要受岩性、沉积微相、成岩作用等因素控制，结合该地区实际情况，将沙二段、沙三段储集层划分为好、中、差3种类型。图4表1参7     

一种基于自然数线性八叉树的优化构造算法

本文提出了一种基于自然数线性八叉树的优化构造算法。该算法以活动结点表为中间辅助结构，在图像输入过程中直接生成基于Ｎ码的八叉树叶结点．与常规构造算法相比，新提出的优化构造算法省去了Ｎ码的计算及合并过程，从而具有较高的时空效率．