高能 X 射线工业 CT 技术的研究进展

目的 研究分析了国内外高能X射线工业CT技术的进展情况，方法 通过有关文献资料，对目前国际上主要的高能X射线工业CT技术及设备进行评述。结果和结论 对美国、德国等发达国家的高能X射线工业CT设备、线阵探测器、面陈探测器及重建算法进行了分析。     

基于小波的彩色序列图象压缩编码

此文提出了一种基于小波变换的运动估计算法，时间复杂度比常规算法降低了一个数量级，同时在估值精度上可与常规算法媲美。利用更佳频率分辨率小波分解处理运动补偿余量误差善了复现图象质量。实验结果表明，该算法在高压缩比情况下图象复现质量显著优于ＭＰＥＧ－２，具有广阔的应用前景。     

利用TM图像进行干旱荒漠带牧区土地资源调查

选用TM卫片作为调查基础资料,结合地形图和局部地区大比例尺航片,完成了甘肃河西地域三个牧业县的土地利用现状调查,为遥感技术在干旱荒漠地带牧区进行土地资源调查找出了效果好、经济的方法。     

Implementation of a vector quantization codebook design technique based on a competitive learning artificial neural network

We describe an implementation of a vector quantization codebook design algorithm based on the frequencysensitive competitive learning artificial neural network. The implementation, designed for use on high-performance computers, employs both multitasking and vectorization techniques. A C version of the algorithm tested on a CRAY Y-MP8/864 is discussed. We show how the implementation can be used to perform vector quantization, and demonstrate its use in compressing digital video image data. Two images are used, with various size codebooks, to test the performance of the implementation. The results show that the supercomputer techniques employed have significantly decreased the total execution time without affecting vector quantization performance.This work was supported by a Cray University Research Award and by NASA Lewis research grant number NAG3-1164.     

外焊缝自动跟踪系统

介绍了外焊缝自动跟踪系统的组成及工作原理，简述了传动部分ＧＴＲ－ＰＷＭ调速系统，给出了系统的硬件电路。该跟踪器具有结构简单，体积小，性能稳定等特点，在生产线上获得了成功的应用。     

CCD应用中的高速图象数据采集技术

介绍了一种可用于精密光学测量的高速线阵ＣＣＤ图象数据采集系统，给出了系统组成、各单元设计考虑和主要技术指标。     

血管数字减影图象中的结构特征提取

基于Ｘ线数字减影图象的三维血管结构重建很大程度上依赖于图象中血管的有效检测和结构关系描述。本文给出一个在局部特征检测基础上的结构特征提取和组织方法，涉及结构分析之前的中间视觉处理层次，即将图象中主要结构分离出来供结构分析之用。首先用一个突出结构检测算法独立地组织和选择中轴曲线片断和边缘曲线片断，然后将两者信号相结合以验证突出结构算法获得的结果并滤除噪声结构。     

小波变换在红外图象处理中的应用

小波变换近年来在图象处理中的应用日益受到人们的关注。小波变换可能同时在时间（或空间）和频率域对信号进行分析，是多分辨率分析的有力工具。本文介绍了小波变换在红外图象处理中的应用，例如红外／可见光图象的配准与融合，红外图象增强，红外图像中的微弱目标探测等。     

Probabilistic linear models for multiresolution estimation in gray-level images

A multiresolution analysis of digital gray-level images is presented. A gray-level multi-scale framework is determined from two main assumptions: the gray scale is binary at the finest spatial resolution, and the gray levels of composed regions are obtained additively. In order to interrelate the gray-level histograms of the same image at different resolutions, probabilistic linear models are developed, which are then applied for estimation. Linear-optimization theory is used as a way of constructing such models. A general procedure for image processing is sketched, based on gray-level estimation. A versatile algorithm for nonlinear filtering is derived. Some examples of prospective applications are given.This work was partially supported by grant TIC91-646 from the DGYCIT of the Spanish Government.     

Fast and Compact 16 by 16 Cellular Neural Network Implementation

The paper presents a Cellular Neural Network implementation based on a high gain sigmoid operation. The required simplifications to the original theory are described that allow the use of high gain. With this design black and white images can be processed. The basic building blocks in a cell are described. A 16×16 cells network has been designed and processed with 1.2 micron CMOS technology. Measurement results which show the operation of the network are presented.