Morphological Pyramids in Multiresolution MIP Rendering of Large Volume Data: Survey and New Results

We survey and extend nonlinear signal decompositions based on morphological pyramids, and their application to multiresolution maximum intensity projection (MIP) volume rendering with progressive refinement and perfect reconstruction. The structure of the resulting multiresolution rendering algorithm is very similar to wavelet splatting. Several existing classes of pyramids are discussed, and their limitations indicated. To enhance the approximation quality of visualizations from reduced data (higher levels of the pyramid), two approaches are explored. First, a new class of morphological pyramids, involving connectivity enhancing operators, is considered. In the pyramidal analysis phase, a conditional dilation operator is used, with a given number n of iterations. The corresponding pyramids for n = 0 and n = 1 are known as the adjunction pyramid and Sun-Maragos pyramid, respectively. We show that the approximation quality when rendering from higher levels of the pyramid does increase as a function of the number of iterations n of the conditional dilation operator, but the improvement for n > 1 is limited. The second new approach, called streaming MIP-splatting, again starts from the adjunction pyramid. The new element is that detail coefficients of all levels are considered simultaneously and are resorted with respect to decreasing magnitude of a suitable error measure. All resorted coefficients are projected successively, until a desired accuracy of the resulting MIP image is obtained. We show that this method outperforms the previous methods based on morphological pyramids, both with respect to image quality with a fixed amount of detail data, and in terms of flexibility of controlling approximation error or computation time.Jos B.T.M. Roerdink received his M.Sc. (1979) in theoretical physics from the University of Nijmegen, the Netherlands. Following his Ph.D. (1983) from the University of Utrecht and a two-year position (1983–1985) as a Postdoctoral Fellow at the University of California, San Diego, both in the area of stochastic processes, he joined the Centre for Mathematics and Computer Science in Amsterdam. There he worked from 1986–1992 on image processing and tomographic reconstruction. He was appointed associate professor (1992) and full professor (2003), respectively, at the Institute for Mathematics and Computing Science of the University of Groningen, where he currently holds a chair in Scientific Visualization and Computer Graphics. His current research interests include morphological image processing, biomedical visualization, neuroimaging and bioinformatics.     

基于VFW视频捕获的运动检测技术

提出了一个基于VFW视频捕获的实时运动检测方案，VFW技术的使用提高了视频捕获的灵活性，减少了对视频设备的依赖。利用命名管道技术来提高图象传送的实时性，通过背景自适应技术可以完整地提取运动目标，实验结果表明所述的方法，对光照、背景内容的变化不敏感，这种方法已经较好地应用于运动跟踪技术研究项目中。     

Asymptotic behavior of morphological filters

The connection between morphological and stack filters is used in the analysis of the statistical properties of morphological filters. Closed-form expressions for the output distributions of morphological filters are given, and their statistical symmetry properties are analyzed. Asytotically tight bounds on the expectations of two-dimensional morphological filters, and asymptotic formulas for the variances of one-dimensional morphological filters are derived. These results form the basis for analyzing general asymptotic properties of morphological filters.     

MLM形态神经网络在彩色图像恢复中的应用

目前彩色图像的恢复方法多集中在加强色彩相似性的研究上。提出了一种基于形态神经网络MLM的图像恢复法,利用非线性的形态神经元算子对噪声图像进行处理,以获得高质量的清晰图像。仿真结果表明,采用本法恢复的图像在连续性及细节的保护上优于其人方法。     

一种改进的针对退化文本图像的二值化方法

在经典的Niblack方法的基础上提出了一种改进的针对退化文本图像的二值化方法,该方法仅在文本区域周围较小范围内进行局部阈值计算,在大大减少运算量的同时,克服了Niblack方法容易产生大量背景噪声的缺点,与另外一种同样基于Niblack的Sauvola方法相比较,对于低对比度的退化文本图像有更好的适应性。     

基于分块投影和形态学处理的多车牌定位方法

针对多车牌定位中候选区域过多和结构元素选择不合理的问题,提出了一种基于分块投影和形态学分块处理的多车牌定位方法。对车牌图像进行预处理和水平差分处理,应用分块水平投影方法粗略定位车牌区域,用形态学分块处理确定车牌的候选区域,最后用车牌的特征去除伪车牌,定位出多个车牌。仿真实验结果表明,该方法能减少车牌候选区域,提高多车牌定位的效率。     

基于粘着性模糊规则的维汉机器翻译最大熵调序研究

针对维汉机器翻译中未登录词和译文乱序问题严重的现象, 结合维吾尔语粘着性语言特点以及最大熵分类算法, 提出了一种基于粘着性模糊规则的维汉机器翻译最大熵调序模型。该模型以最大熵模型为基础, 在维吾尔语词级别构建粘着性规则约束, 从训练语料中提取更加有效的调序规则来指导翻译解码过程。实验证明, 与当前主要MSD(mono、swap、discontinuous)等调序方法相比, 该方法较好地体现了维吾尔语的粘着性特点, 提高了译文质量。     

AAO模板浸渍法制备Au纳米线

用模板浸渍法成功地在多孔阳极氧化铝(AAO)模板里制备了Au纳米线。在这种方法中,AAO模板的孔壁在HAuCl4里浸湿,取出后通过热处理形成Au纳米线。使用扫描电子显微镜和X射线对Au纳米线的微观形貌和结构进行了表征。扫描电镜图片表明在AAO孔中形成了直的并且表面粗糙的金纳米线,纳米线直径约50 nm。X射线衍射图表明,金纳米线具有面心立方(FCC)结构。最后,研究了Au纳米线的形成机理。     

风暴作用下淤泥质潮滩-潮沟系统地貌演变研究进展

鉴于风暴作用对淤泥质潮滩-潮沟系统的地貌演变有重要的影响,对海岸工程的安全以及海岸带资源的开发与保护有重要的实用价值,从研究方法、演变特点和动力机制等方面回顾了风暴作用下淤泥质潮滩-潮沟系统地貌演变的研究进展。认为淤长型潮滩风暴剖面的形态特征一般呈"中间冲刷,两端淤积",但其动力机制研究系统性还不够;盐沼可以较好地削弱风暴,起到固沙效果,但其侧向演变值得进一步关注;风暴作用下潮沟的活动性大大增强,其中潮沟摆动及其岸壁侵蚀机理是亟待解决的科学问题。指出未来应进一步加强现场资料的获取,并通过数值模拟、物理模型试验等手段,加强对风暴作用下潮滩-潮沟系统地貌演变机理的研究。     

Morphological,thermal, rheological and noodle‐making properties of potato and corn starch

A comparison between the morphological, thermal, rheological and noodle‐making properties of corn starch and potato starches separated from five different potato cultivars was made. The granule size and shape of all starches differed significantly. Potato starch granules were comparatively larger than corn starch granules, while the transition temperatures were found to be higher for corn starch. Consistency coefficients and flow behaviour indices measured by back extrusion were higher for potato starches than for corn starch. Stickiness of cooked starch pastes was observed to depend upon their consistency coefficient. The gels made from all potato starches showed higher gel strength than those from corn starch. The gel strength of starches from both corn and potato increased during refrigerated storage. The amylose content, swelling power, solubility and light transmittance values of potato starches were significantly higher than those of corn starch. Noodles made from potato starches had higher cooked weight and cooking loss than corn starch noodles. Texture profile analysis revealed that potato starch noodles also had higher hardness and cohesiveness than corn starch noodles. Hardness of cooked noodles from all starches increased and cohesiveness decreased during storage. Noodles made from starches of higher viscosity exhibited higher hardness and cohesiveness. Textural differences among cooked starch noodles appeared to be associated with morphological, thermal and rheological properties of corn starch and potato starches. © 2002 Society of Chemical Industry