高灵敏度荧光显微镜及其在细胞光敏效应研究中的应用

研制了一种可探测极微弱细胞荧光图象的高灵敏度荧光显微镜，在仪器中使用了一个高质量的亮度增益为５０，０００的象增强器对细胞的荧光图象进行光能量放大，因而这种荧光显微镜可探测到普通荧光显微镜不能观察的微弱荧光图象。由于仪器中光源的输出强度很小，避免了长时间观察对活细胞的光损伤，并可观察到荧光效率低的荧光物质的分布图象。探测系统中用计算机采集图象数据，同时对数据进行必要处理，以提高图象的质量。这种高灵敏度的荧光显微镜可用于分析细胞中荧光物质的分布，以及细胞动态生理过程的研究。使用此仪器已直接观察到光敏竹红菌甲素在Ｈｅｌａ细胞（人体宫颈癌细胞）中的分布，细胞受光照射后的光损伤现象及加入三种细胞保护剂后获得不同程度保护的细胞状态。     

同心球所夹空间电场的电像法求解

采用电像法分析研究了二同心导体球所夹空间的静电场分布。     

形态学边缘检测的新算法及其应用

提出了一种基于数学形态学的边缘检测的所算法，该算法具有简便和灵活可编程控制等优点，比原来主算法更国完善，在实际应用中有着很好的前景，并给出了实验结果。     

数字图像边缘检测算子的性能实验比较

本文对数字图像中几种具有代表性的边缘检测算子进行了理论分析，并通过VC编程实验，对各种算法进行实现，通过比较得出了各自的优缺点和适用范围。     

Nonlinear filtering structure for image smoothing in mixed-noise environments

This paper introduces a new nonlinear filtering structure for filtering image data that have been corrupted by both impulsive and nonimpulsive additive noise. Like other nonlinear filters, the proposed filtering structure uses order-statistic operations to remove the effects of the impulsive noise. Unlike other filters, however, nonimpulsive noise is smoothed by using a maximum a posteriori estimation criterion. The prior model for the image is a novel Markov random-field model that models image edges so that they are accurately estimated while additive Gaussian noise is smoothed. The Markov random-field-based prior is chosen such that the filter has desirable analytical and computational properties. The estimate of the signal value is obtained at the unique minimum of the a posteriori log likelihood function. This function is convex so that the output of the filter can be easily computed by using either digital or analog computational methods. The effects of the various parameters of the model will be discussed, and the choice of the predetection order statistic filter will also be examined. Example outputs under various noise conditions will be given.     

森林火情监测预报研究

对现行的森林火情监测方法进行了分析比较。根据实际存在的难题，提出了料为产用的实施方案及应采取的技术措施，进行了实地试验，取得较好的效果。     

Radiosity with Well Distributed Ray Sets

In this paper we present a new radiosity algorithm, based on the notion of a well distributed ray set (WDRS). A WDRS is a set of rays, connecting mutually visible points and patches, that forms an approximate representation of the radiosity operator and the radiosity distribution. We propose an algorithm that constructs an optimal WDRS for a given accuracy and mesh. The construction is based on discrete importance sampling as in previously proposed stochastic radiosity algorithms, and on quasi Monte Carlo sampling. Quasi Monte Carlo sampling leads to faster convergence rates and the fact that the sampling is deterministic makes it possible to represent the well distributed ray set very efficiently in computer memory. Like previously proposed stochastic radiosity algorithms, the new algorithm is well suited for computing the radiance distribution in very complex diffuse scenes, when it is not feasible to explicitly compute and store form factors as in classical radiosity algorithms. Experiments show that the new algorithm is often more efficient than previously proposed Monte Carlo radiosity algorithms by half an order of magnitude and more.     

Speed-up fractal image compression with a fuzzy classifier

This paper presents a fractal image compression scheme incorporated with a fuzzy classifier that is optimized by a genetic algorithm. The fractal image compression scheme requires to find matching range blocks to domain blocks from all the possible division of an image into subblocks. With suitable classification of the subblocks by a fuzzy classifier we can reduce the search time for this matching process so as to speedup the encoding process in the scheme. Implementation results show that by introducing three image classes and using fuzzy classifier optimized by a genetic algorithm the encoding process can be speedup by about 40% of an unclassified encoding system.     

图象信息与光电子技术

本文阐述图象信息的重要性，说明它与光电子技术的关系，包括图象信息的获取、传输、存储与显示，展望了未来。     

地层微电阻率成像测井在中原油田的应用

介绍地层微电阻率测井(FMI)技术以及它在地质构造解释、沉积学解释、裂缝识别、地层分析等方面独特的枝术优势,并详细介绍了FMI在中原油田濮深X井的实际应用,进行了应用效果分析,指出成像测井是未来油田油气勘探开发的重要技术手段。