太赫兹单像素计算成像原理及其应用(特邀)

太赫兹成像技术具有透视性、安全性以及光谱分辨能力等独特优点,有着广泛的应用前景。由于太赫兹面阵探测器的技术成熟度低、价格昂贵,太赫兹成像技术在较长时间内以单点扫描方案为主,存在系统复杂、成像耗时长等问题。近年来,基于计算成像算法的太赫兹单像素成像技术发展迅速,成为了获取太赫兹图像的重要途径之一。文章综述了太赫兹单像素计算成像技术的基本原理、技术实现手段和应用前景,总结了现存的一些关键问题,并展望了一些今后可能的发展方向。

激光散斑的亚像素位移法计算及比较

根据激光散斑相关测量中采用的插值法、梯度算法和牛顿-拉夫森迭代法3种亚像素位移算法的特点,逐一在亚像素尺度计算出磁流体干燥过程中的同一激光散斑图的偏均值和标准差变化曲线。基于得到的偏差均值和标准差讨论了3种算法处理激光散斑图的特点,比较了3种算法处理散斑图的计算精度、稳定性和计算用时。结果显示,在小变形的亚像素位移测量时,梯度算法的精度较高,且较为稳定,计算效率也较牛顿-拉夫森算法快约9倍。因此,在进行小变形亚像素位移测量时,采用梯度算法计算激光散斑是有效的。

精密器件尺寸的图像测量算法设计与实现

为了实现精密器件的无接触精密快速测量,本文提出了一种利用精密器件图像对进行尺寸测量的方法。根据不同的参照物的比例关系及采用不同倍率的图像预处理测量算法,实现两点的距离、测量斜率、角度、半径、曲线弧度的测量。实验的结果表明,本文提出的图像测量算法具有灵活性高、测量结果准确的优点。

一种基于LBP改进的人脸识别算法

针对局部二值模式(local binary pattern,LBP)算法的缺陷,提出了一个改进算法LBP_Gao.在像素计算、重点区域的权重、重点区域遮盖等方面进行了改进.通过仿真实验证明,改进后的算法具有较高的识别率和较强的适应能力.

基于参数空间的混合多分辨率绘制

根据点和多边形在表示和绘制物体上各自不同的特点,提出了一种有效绘制细节高度复杂物体的多分辨率方法.3D表面被映射到参数平面,经规则采样成为几何图像,P-Quadtrees是基于几何图像建立的四叉树多分辨率层次结构.通过对四叉树的遍历,面向视点的表面用较大多边形面片绘制,光照细节通过法向映射完成;轮廓部分通过视点相关的LOD(level of detail)控制进行细化,使用点来绘制物体复杂精细的轮廓.通过此方法,细节复杂模型的绘制不仅可以被硬件加速,而且无论在表面还是在轮廓部分都能获得很好的视觉效果.

Color image segmentation using mean shift and improved ant clustering

To improve the segmentation quality and efficiency of color image,a novel approach which combines the advantages of the mean shift(MS) segmentation and improved ant clustering method is proposed.The regions which can preserve the discontinuity characteristics of an image are segmented by MS algorithm,and then they are represented by a graph in which every region is represented by a node.In order to solve the graph partition problem,an improved ant clustering algorithm,called similarity carrying ant model(SCAM-ant),is proposed,in which a new similarity calculation method is given.Using SCAM-ant,the maximum number of items that each ant can carry will increase,the clustering time will be effectively reduced,and globally optimized clustering can also be realized.Because the graph is not based on the pixels of original image but on the segmentation result of MS algorithm,the computational complexity is greatly reduced.Experiments show that the proposed method can realize color image segmentation efficiently,and compared with the conventional methods based on the image pixels,it improves the image segmentation quality and the anti-interference ability.

A New Software for GIS Image Pixel Topographic Fac－tors in Remote Sensing Monitoring of Soil Losses

Based on the new algorithm for GIS image pixel topographic factors in remote sensing monitoring ofsoil losses, a software was developed for microcomputer to carry out computation at a medium river basin(county). This paper lays its emphasis on algorithmic skills and programming techniques as well as applicationof the software.

Video Image Block-matching Motion Estimation Algorithm Based on Two-step Search

Aiming at the shortcoming that certain existing blockingmatching algorithrns, such as full search, three-step search, and dia- mond search algorithms, usually can not keep a good balance between high acoaracy and low computational complexity, a block-maching motion estimation algorithm based on two-step search is proposed in this paper. According to the fact that the gray values of adjacent pixels will not vary fast, the algorithm employs an interlaced search pattem in the search window to estimate the motion vector of the objectblock. Simulation and actual experiments demanstrate that the proposed algmithm greatly outperforms the well-known three-step search and dianond search algoritlam, no matter the motion vector is large or small. Comparedc with the full search algorithm, the proposed one achieves similar peffomance but requires much less computation, therefore, the algorithm is well qualified for real-time video image processing.

A Fast Clonal Selection Algorithm for Feature Selection in Hyperspectral Imagery

Clonal selection feature selection algorithm （CSFS） based on clonal selection algorithm （CSA）, a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm （FCSFS） for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager （PHI） and the airborne visible/infrared imaging spectrometer （AVlRIS）, respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.