平面分层介质结构全波分析综述

本文综述了广义谱域导抗法，直线法及直线法的快速算法，全波离散镜象法等主要方法，并对各种方法的特点进行了比较，这些方法可有效地处理平面分层介质结构问题，文中包括作者近期的研究成果。     

强度调制／直接检测（IM／DD）光纤通信系统色散限制的研究

通过引入归一化脉宽Ｐ和相对脉冲展宽因子ｑ，提出了一个适用于ＩＭ／ＤＤ系统中各种眼图恶化量ｘ和归一化脉宽Ｐ的色散限制改进公式。通过与其它理论的比较、计算机仿真和对实验数据的分析，验证了该公式的正确性，并给出了其它结果的限制条件。研究表明：当眼图恶化量ｘ为１ｄＢ左右时，对２．５Ｇｂ／；外调制信号（α＝０）而言，非色散位移光纤ＩＭ／ＤＤ系统的色散因子γ约等于０．７９，所对应的系统再生中继距离约为９００余公里。     

A Survey of Inverse Surface Design From Light Transport Behavior Specification

Inverse surface design problems from light transport behavior specification usually represent extremely complex and costly processes, but their importance is well known. In particular, they are very interesting for lighting and luminaire design, in which it is usually difficult to test design decisions on a physical model in order to avoid costly mistakes. In this survey, we present the main ideas behind these kinds of problems, characterize them, and summarize existing work in the area, revealing problems that remain open and possible areas of further research.     

On denoising and compression of DNA microarray images

We address the problems of noise and huge data sizes in microarray images. First, we propose a mixture model for describing the statistical and structural properties of microarray images. Then, based on the microarray image model, we present methods for denoising and for compressing microarray images. The denoising method is based on a variant of the translation-invariant wavelet transform. The compression method introduces the notion of approximate contexts (rather than traditional exact contexts) in modeling the symbol probabilities in a microarray image. This inexact context modeling approach is important in dealing with the noisy nature of microarray images. Using the proposed denoising and compression methods, we describe a near-lossless compression scheme suitable for microarray images. Results on both denoising and compression are included, which show the performance of the proposed methods. Further experiments using the results of the proposed near-lossless compression scheme in gene clustering using cell-cycle microarray data for S. cerevisiae showed a general improvement in the clustering performance, when compared with using the original data. This provides an indirect validation of the effectiveness of the proposed denoising method.     

A New Image Analysis Based Method for Measuring Electrospun Nanofiber Diameter

In this paper, a new image analysis based method for electrospun nanofiber diameter measurement has been presented. The method was tested by a simulated image with known characteristics and a real web. Mean (M) and standard deviation (STD) of fiber diameter obtained using this method for the simulated image were 15.02 and 4.80 pixels respectively, compared to the true values of 15.35 and 4.47 pixels. For the real web, applying the method resulted in M and STD of 324 and 50.4 nm which are extremely close to the values of 319 and 42 nm obtained using manual method. The results show that this approach is successful in making fast, accurate automated measurements of electrospun fiber diameters.     

基于图像的虚拟环境建模技术

综述了基于图像的虚拟现实环境的建模技术，并给出了各种模型表示的理论依据和建模过程的定义。把环境表示分为四类：全景图，光场数据库，深度图像和多投影中心图。全景图的生成包括基于图像相关性和基于图像整合变换的算法。光场数据库的分类主要依据全光函数。同时论述了在各种表示下的采样和建模技术。最后讨论了当前建模技术研究的热点及所需要解决的问题。     

基于非锐化掩模的实时自适应图像增强算法

针对传统的非锐化掩模算法的局限性,依据图像中各像素点及以其为中心的若干相邻像素点的均方差值,提出了自适应图像增强算法的原理,并分析其硬件实现方法,然后给出了该算法与其它算法应用于图像增强的对比结果,最后在FPGA（field programmable gate array）实验板上进行验证.实验结果表明,此算法有效的增强图像的细节区域,防止图像边缘区域出现过冲现象,抑制图像平坦区域的噪声放大.因此,该算法取得了良好的视觉效果,硬件实现简单,适合于实时条件下图像的增强.     

基于Gibbs模型的提高图像分辨率方法

在提高图像分辨率过程中,选择合适的成像模型是获得高分辨率图像的一个关键因素。提出一种基于最大后验概率、采用Gibbs成像模型,并利用多帧序列图像重构高分辨率图像的方法,充分利用序列图像之间的累加信息,从而快速地获得较其他方法更优的高分辨率图像。     

图像奇异值特征矢量缩放不变性分析及应用

图像奇异值特征矢量以其稳定性和它在转置、平移、旋转和镜像变换下具有的不变性,被认为是一种图像的代数特征,广泛应用于图像匹配和图像识别。通过矩阵运算,证明了奇异值特征矢量在图像做缩放变换时具有不变性,并将这种性质运用于图像匹配。实验结果表明这种不变性与奇异值特征矢量在图像做转置、平移、旋转和镜像变换时所具有的不变性一样,是奇异值特征矢量能够作为图像代数特征的一个重要依据。     

Robust图像跟踪：强度—特征混合式目标定位

在像平面上确定目标的位置(由它的瞄准点位置表示)是图像跟踪技术的核心.目前研究的目标是图像定位方法多偏重于单一的工作模式,因而难以适应变化较大的使用环境.本文提出一种旨在综合利用强度相关和特征匹配的混合式目标图像定位方法.假定当前帧图像已经过预处理并完成分割,首先通过一种自适应门限SSDA并辅之以投影排序搜索,尽可能快速地剔除与参考图差别较大的子区;再用一种简便可靠并可具一定记忆能力的特征匹配法,在保留的子区集内,为目标精确定位——宣布瞄准点位置.利用实际序列图像所作实验表明:上述方法较之通常采用的单一工作模式的定位方法,有明显增强的Robust性以及更广的适应性,而增加的计算代价不大.