Improved resolution three-dimensional integral
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磁共振水成像技术对内耳的成像研究及应用研究生:明洁导师:贾文霄教授摘要目的:探讨磁共振水成像技术(Magnetic resonance hydrography MRH)的三种后处理方法,即多平面重建(MPR)、最大密度投影(MIP)、容积再现(VR)对内耳显示分别有各自优势,为不同内耳原因导致的感音神经性耳聋(SNHL)选择简单、合理、有效的扫描序列和最佳后处理方法,为临床无创评估内耳病变及诊断治疗提供客观有效的影像学依据。
方法:对80例无听力障碍的正常人及45例临床确诊为SNHL的患者行高分辨率三维快速自旋回波T2加权序列(3D TSE T2WI)行横断面扫描,然后行3D TSE T2WI双侧斜矢状面扫描。
对45例SNHL患者加扫T1WI,若该序列显示有异常信号则行T1WI扫描。
数据采集后传至工作站利用ViewForum后处理软件行MPR、MIP、VR 重建。
观察正常内耳及内听道解剖结构的显示情况,并进行测量。
应用统计学方法对测量值及不同后处理技术对内耳各解剖结构评分,分别行组间及不同后处理方法间的差异性检验。
结果:(1)正常志愿者组80例160耳均能清晰地显示耳蜗前庭神经、面神经、蜗神经及内耳膜迷路的细微解剖结构。
(2)VR、MIP测量前、水平、后半规管最大径及管径,蜗管管径及最大径差异有统计学意义;VR、MIP图像质量的差异有统计学意义;VR、MIP、MPR显示膜迷路诸结构及神经的能力的差异具有统计学意义;(3)45例病人中MRI内耳发现有9例异常(阳性率20%),共7种病变,其中儿童(小于14岁)以先天性异常-前庭导水管扩大(3例)最常见。
结论:(1)内听道及膜迷路的细微结构可利用磁共振内耳水成像技术得以立体而直观的显示,具有其他方法不可替代的作用;(2)MRH对SNHL病因的诊断有很好的指导作用,是有效的影像学检查方法;(3)在多种内耳水成像技术的后处理方法中,MPR在显示神经方面具有优势,VR在观察膜迷路形态方面更具优势,其图像更清晰,与周围结构的毗邻关系显示的更加确切,能对内耳形态是否具有改变进行更有效地评估。
物探专业术语1、观测系统测线上激发点和接收点的相对位置关系。
为了得到能够系统地追踪目的层有效波的地震记录,在野外资料采集时必须适当地安排和选择激发点与接收点的相互位置,即要选择合理的观测系统。
2、二维地震勘探沿着地表的一条直线进行勘测,就能够研究该测线下面不同地层界面的形状和位置,这种勘测方法称为二维地震勘探,相应的观测系统称为2D观测系统。
3、三维地震勘探如果在地表的某一平面内连续地进行观测,就能够最佳地研究该平面下不同地震界面的形状和位置,这种勘测方法称为三维地震勘探,相应的观测系统称为3D观测系统。
4、多次覆盖对界面上某一点进行观测称为采样或覆盖。
若对每个点只观测一次,称为单次覆盖,如观测多次,则称为多次覆盖。
5、覆盖次数对界面上某一点进行观测的次数。
覆盖次数的设计:假如目的层反射波能量强,连续性好,能够可靠地追踪,那么每个反射点只需要勘测一次就足够了。
但是实际情况并非如此,有效反射波总是与各种干扰波重叠干涉。
当勘探深度增大时,由于多次波和散射波相对加强,信噪比变得更低,单次覆盖效果不佳,因此现在广泛采用多次覆盖系统。
基本思路:用一组单次覆盖系统,其中每一种都可以沿侧线连续追踪同一反射界面,当资料处理合适时,反射层应该位于每个地震剖面的相同地段。
6、炸药震源炸药震源是脉冲震源。
炸药在外界的影响下迅速放出气体和高热,形成高压气团而急剧膨胀,在很短的瞬间将冲击力作用于周围物体,即形成所谓的冲击波。
在爆炸中心,物体被粉碎、破坏或产生非弹性形变。
在破坏带及非弹性形变带外,形成岩石的弹性变带,此时冲击波变成弹性波传播出去。
常用的炸药是硝氨炸药。
经验表明,炸药激发的地震振动是衰减很快的似正弦脉冲,脉冲的前缘很陡,能量高度集中。
在均匀介质中爆炸时形成中心对称的膨胀型震源,主要产生纵波。
7、可控震源这是50年代问世的一种新型震源,因为它产生一个延续时间从几秒到几十秒,频率随时间变化的正弦振动,故称为连续振动震源;又因为扫描的频率范围及振动的延续长度都可以事先控制和改变,故称可控震源。
精品文档Glossary of《Introduction to Modern Photogrammetry》《当代摄影测量》双语教学词汇表AAbbe comparator principle阿贝比长原理aberration 像差absolute flying height 绝对航高absolute orientation 绝对定向absorption 吸收access 存取、访问accessory 附件、辅助设备accident error 偶然误差accuracy 精度、准确度accuracy assessment 精度评定acquisition 获取active remote sensing 主动式遥感adaptability 适应性adjustment 平差adjacent 邻接adjacent flight line 相邻航线adjacent area 邻接区域adjoining sheets 邻接图幅aerial camera 航空摄影机aerial photograph 航摄像片aerial photographic gap 航摄漏洞aerial photogrammetry航空摄影测量aerial remote sensing 航空遥感aerophotogrammetry 航空摄影测量aerotriangulation 空中三角测量block triangulation区域网三角测量strip triangulation航带法空中三角测量independent model triangulation独立模型法空中三角测量bundle triangulation光束法空中三角测量affine rectification 仿射纠正affined transformation 仿射变换aggregation 聚合、聚集air base 摄影基线airbone imagery 机载影像airborne sensor 机载传感器alignment 排列成行、对准algebra 代数algorithm 算法allocation 配置altimeter 测高仪altitude 高度、高程ambiguity 模糊、不定性anaglyph 互补色anaglyphical stereoscopic viewing互补色立体观察analog 模拟analog/digital conversion 模数转换analog photogrammetry 模拟摄影测量analytical aerotriangulation解析空中三角测量analytical photogrammetry 解析摄影测量analytical plotter 解析测图仪ancillary data 辅助数据angular field of view 像场角angular momentum 角动量animation 动画annotation 注释、注记annotated photograph 调绘像片aperture 光圈、孔径relative ~ 相对孔径effective ~ 有效孔径approximation 近似值、逼近archive 档案archiving 存档architectural photogrammetry建筑摄影测量archaeological photogrammetry考古摄影测量artificial intelligence 人工智能artificial target 人工标志(点)aspect 方位aspect map 坡向图assessment 评定、估价astigmatism 像散atlas 地图集atmospheric haze 大气蒙雾atmospheric refraction 大气折光atmospheric window 大气窗口atmospheric transmission 大气传输atmospheric transmissivity 大气透过率attenuation 衰减attitude 姿态attitude parameter 姿态参数attribute 属性autocollimation 自准直autocorrelation 自相关automatic triangulation自动空中三角测量azimuth angle 方位角azimuth resolution 方位角分辨率Bbackprojection 逆投影backup 备份ballistic camera 弹道摄影机ballistic photogrammetry弹道摄影测量bandwidth 波段宽barrel 圆筒、桶形失真baseline 基线base-height ratio 基-高比batch process 批处理baud rate 波特率Bayes classification 贝叶斯分类bilinear interpolation 双线性内插binary image 二值影像biomedical photogrammetry生物医学摄影测量biostereometrics 生物立体量测学black-and-white film 黑白片blinking method of stereoscopic viewing 闪闭法立体观察block adjustment 区域网平差blunder detection 粗差探测bulk processing 粗处理bundle of rays 光束boundary 边界breakline 断裂线bridging of models 模型连接brightness 亮度Ccadastral mapping 地籍制图calibration 检校camera calibration 摄影机检校carrier phrase measurement载波相位测量Cartesian coordinates 笛卡尔坐标cartography 地图学characteristic curve of photographic emulsion 感光特性曲线check point 检查点chromatic 彩色的classification 分类classifier 分类器close-range photogrammetry近景摄影测量clustering 聚类cognitive mapping 认知制图collinearity condition 共线条件collinearity equations 共线方程color enhancement 彩色增强color infrared film 彩色红外片color film 彩色片coma 彗星像差combined adjustment 联合平差comparator 坐标量测仪compensation 补偿complementary colors 互补色component 组件、分量compression 压缩computer aided mapping 机助测图computer vision 计算机视觉computer-aided cartography计算机辅助制图condition equations 条件方程confidence 置信度coverage 覆盖conformal 正形的、等角的contact printing 接触晒印content of information 信息量contour lines 等高线contour interval 等高距constraint 约束contrast enhancement 反差增强contrast coefficient 反差系数control point 控制点control photostrip 骨架航线convergent photography 交向摄影convolution operators 卷积算子coordinate grid 坐标格网coordinate system 坐标系photographic coordinate system 像平面坐标系image space coordinate system 像空间坐标系object coordinate system物方坐标系coplanarity equation 共面方程correlation efficient 相关系数corresponding image point 同名像点corresponding image rays 同名光线corresponding epipolar line 同名核线cosine transformation 余弦变换covariance 协方差covariance matrix 协方差矩阵crest 山脊、峰顶cross-section 断面cyberspace 信息空间、赛博空间cycle slip 周跳Ddata acquisitation 数据获取data compression 数据压缩data mining 数据挖掘data snooping 数据探测法data transmission 数据传输data processing 数据处理data warehouse 数据仓库datum 基准deformation 变形densitometer 密度计density slicing 密度分割depression 抑制、衰减depth of field 景深detector 探测器developing 显影diagonal matrix 对角矩阵diaphragm 光圈differential 差分differential method of photogrammetric mapping 分工法测图differential rectification 微分纠正diffraction 衍射diffusion 扩散、漫射digital/analog transform 数/模转换digital correlation 数字相关digital earth 数字地球digital image 数字影像digitizer 数字化器digitization 数字化digitized image 数字化影像digital mapping 数字测图digital mosaic 数字镶嵌digital surface model数字表面模型(DSM)digital terrain model数字高程模型(DTM)digital orthophoto map数字正射影像(DOM)digital orthoimage 数字正射影像digital photogrammetry 数字摄影测量digital raster graphic数字栅格地图(DRG)digital rectification 数字纠正digital tracing table 数控绘图桌dimensional 维one- dimensional一维的two- dimensional 二维的three- dimensional 三维的disparity 不同、差异displacement of image 像点位移distortion of lens 物镜畸变差distribution function 分布函数direct line transformation直接线性变换(DLT)direct scheme of digital rectification直接法纠正direction cosines 方向余弦discrimination 辨别、区分dispersion 分散、散射drainage 水系drawing 绘图drift angle 偏流角dynamic 动态的Eearth curvature 地球曲率earth ellipsoid 地球椭球eccentricity 偏心、偏心率edge detection 边缘检测edge enhancement 边缘增强eigenvalue 特征值eigenvector 特征向量electromagnetic spectrum 电磁波谱elements of interior orientation内方位元素elements of exterior orientation外方位元素elements of relative orientation相对定向元素elements of absolute orientation绝对定向元素elements of rectification 纠正元素emulsion 药膜encoding 编码enhancement 增强entity 实体entropy (信息)熵entropy coding 熵编码environment 环境epipolar line 核线epipolar plane 核面epipolar correlation 核线相关epipolar resampling 核线重采样epipole 核点equalization of histogram 直方图均衡equivalent vertical photograph等效竖直像片equally tilted photography 等倾摄影error circle 误差圆Ethernet 以太网expert system 专家系统ES exposure 曝光exposure station 摄站exponential 指数的exterior orientation 外部定向event 事件Ffalse color film 假彩色片false color photography 假彩色摄影false color composite 假彩色合成feature 特征feature coding 特征编码feature extraction 特征提取feature selection 特征选择fiducial marks 框标mechanical fiducial marks机械框标optical fiducial marks光学框标field curvature像场弯曲field of view 视场filtering 滤波fixing 定影flight block 摄影分区flight height (flying height)航高flight line 摄影航线flight plan of aerial photography航摄计划flight strip 航带flying height 航高absolute ~ 绝对航高relative ~ 相对航高flying trace 航迹floating mark 浮游测标flux 通量、流动focal distance 焦距focal length 焦距focal plane 焦平面format 像幅forward motion compensation (FMC)向前运动补偿Fourier transformation 傅立叶变换fractal 分数维frame camera 框幅式摄影机free net adjustment 自由网平差frequency 频率Fresnel 菲滠耳fuzzy classifier method 模糊分类法fuzzy image 模糊影像GGaussian distribution 高斯分布generalization 综合geodetic origin 大地原点generation 产生geodetic datum 大地基准geodetic database 大地测量数据库geocentric coordinate system地心坐标系geodetic origin 大地原点geodetic datum 大地基准geographic coding 地理编码geoid 大地水准面geomatics 测绘学geometric correction 几何校正geometric rectification 几何纠正geometric registration of image图像几何配准geometric model 几何模型geostationary 地球静止的geo-synchronous satellite 地球同步卫星gnomonic 球心的goniometer 测角器、测向器gradients 梯度graphic 图形的grating 格子、光栅gravity 重力grey level 灰度级grey scale 灰度级grey wedge 光契grid 格网ground nadir point 地底点gross error detection 粗差检测GPS aerotriangulation GPS空中三角测量Gruber point 标准配置点Hheight displacement 投影差high-pass filtering 高通滤波histogram equalization 直方图均衡histogram 直方图histogram specification直方图规格化histogram equalization直方图均衡化hologram photography 全息摄影hologrammetry 全息摄影测量homogeneous 均质的、齐次的homologous image point 同名像点homomorphic filtering 同态滤波horizon camera 地平线摄影机horizontal 水平的、平面的horizontal parallax 左右视差(x-parallax)horizontal parallax difference左右视差较hot spots 热点hough transformation 霍夫变换Huffman 霍夫曼hue 色度hypergraph 超图hypermedia 超媒体hyperspectral 高光谱、超光谱hypertext 超文本hypothesis 假设Iidentified photograph 调绘片index contour 计曲线illuminance of ground 地面照度image,imagery 影像image coding 影像编码image correlation 影像相关image description 影像描述image digitization 影像数字化image enhancement 影像增强image fusion 影像融合image interpretation 影像解译image matching 影像匹配image mosaic 影像镶嵌image motion compensation像移补偿image overlaying 影像复合image pyramids 影像金字塔image quality 影像质量image recognition 影像识别image registration 影像配准image resolution 影像分辨力image restoration 影像复原image motion compensation像移补偿(IMC)image segmentation 图像分割image space coordinate system像空间坐标系image transformation 图像变换image understanding 图像理解imaging equation 构像方程imaging radar 成像雷达imaging spectrometer 成像光谱仪incident angle 入射角independent model aerial triangulation 独立模型法空中三角测量indirect scheme of digital rectification 间接法纠正industrial photogrammetry工业摄影测量inertial measurement unit (IMU)惯性测量装置information extraction 信息提取infrared film 红外片infrared photography 红外摄影infrared remote sensing 红外遥感infrared scanner 红外扫描仪inner 内部的inner orientation 内定向instrument 仪器、设备integration 集成intensity 亮度interactive 交互interest point 兴趣点、有利点interferogram 干涉图interferometry 干涉测量学interior orientation 内部定向interometry SAR 干涉雷达(INSAR)interoperability 互操作interpolation 内插bilinear interpolation 双线性内插nearest-neighbor interpolation邻近像元内插invariant 不变量irradiance 辐射照度isocenter of photograph 像等角点isometric 等角、等值的isometric parallel 等比线iteration method 迭代法iteration method with variable weights选权迭代法intersection 相交inverse matrix 逆矩阵Kkey-in 键盘输入key word 关键字kinematic positioning 动态定位knickpoint 转折点、裂点Llaboratory 实验室Landsat 陆地卫星landform 地形landscape map 景观地图large format camera大像幅摄影机(LFC)latent 潜在的lateral tilt 旁向倾角(roll)lateral overlap(side overlap,side lap)旁向重叠layover 雷达图像移位least squares correlation最小二乘相关leveling of model 模型置平linear array sensor 线阵列传感器linear features 线特征linear transformation 线性变换linearization 线性化logarithmic 对数的longitudinal tilt 航向倾角(pitch)longitudinal overlap(end overlap,forward overlap)航向重叠low-pass 低通Mmagazine 暗盒magnification 放大manual 人工的manuscript map 原图map compilation 地图编辑map legend 图例map projection 地图投影map revision 地图更新mapping satellite 测图卫星marine charting 海洋测绘mathematical expectation 数学期望maximum likelihood classification最大似然分类matrix 矩阵mean square error 中误差measuring mark 测标mechanics 力学median filters 中值滤波器mesh 网、网格metadata 元数据meteosat 气象卫星minimum distance classification最小距离分类metric camera 量测摄影机microwave remote sensing 微波遥感method of least squares 最小二乘法microwave radiation 微波辐射microwave radiometer 微波辐射计modulation transfer function调制传递函数(MTF)moiré莫尔条纹monocomparator 单像坐标量测仪mount 安装、座架mosaic 镶嵌optical mosaic 光学镶嵌digital mosaic 数字镶嵌most probable value 最或然值multicollimator 多投影准直仪multiplex 多倍仪multistage rectification 多级纠正multispectral camera 多光谱摄影机multispectral photography多光谱摄影multispectral remote sensing多光谱遥感multispectral scanner多光谱扫描仪(MSS)multi-temporal analysis 多时相分析multi-temporal remote sensing多时相遥感multiplicity 多重性、相重性Nnadir point 底点navigation 导航negative 负片neighborhood method 邻元法nodal point 节点front nodal point 前节点rear nodal point 后节点neutral network 神经网络nonlinear 非线性的non-metric camera 非量测摄影机non-topographic photogrammetry非地形摄影测量normal case photography 正直摄影normal distribution 正态分布normal equation 法方程式normalization 正交化Ooblique 倾斜的oblique photography 倾斜摄影object space coordinate system物空间坐标系object spectrum characteristics地物波谱特性object oriented 面向对象observation 观测值observation equation 误差方程式occlusion 遮蔽offset 移位off-line 离线、脱机on-line 在线、联机on-line aerial triangulation联机空中三角测量one-dimensional 一维的opacity 不透明的operator 算子optical axis of lens 物镜主光轴optical rectification 光学纠正optical-mechanical rectification光机械学纠正optical projection 光学投影optical transfer function光学传递函数(OTF)orthogonal matrix 正交矩阵orientation elements 方位元素orientation point 定向点orthogonal projection 正射投影orthographic 正射的orthogonal matrix 正交矩阵orthoimage 正射影像orthophoto 正射像片orthophotomap 正射影像地图orthophoto stereomate正射影像立体配对片orthophoto technique 正射影像技术outline map 略图outstanding point 明显地物点overlap 重叠Ppackage 包panchromatic film 全色片panoramic camera 全景摄影机panoramic photography 全景摄影panoramic distortion 全景畸变parallax 视差parallax difference 视差较parallel-averted photography等偏摄影parameter 参数parameter estimation 参数估计pass point 加密点pattern recognition 模式识别perceived model 视模型perigee 近地点perspective center 透视中心phase transfer function相位传递函数(PTF)photogrammetric distortion摄影测量畸变差photogrammetric workstation摄影测量工作站photogrammetry 摄影测量terrestrial ~ 地面摄影测量two-medium ~ 双介质摄影测量biomedical ~ 医学摄影测量photography 摄影学photographic baseline 摄影基线photographic bundle of rays 摄影光束photographic coordinate system摄影测量坐标系photographic interpolation摄影测量内插photographic paper 相纸photographic processing 摄影处理photographic scale 摄影比例尺photo base 像片基线photo coordinate system像平面坐标系photo interpretation 像片判读photo map 像片平面图photo mosaic 像片镶嵌photo nadir point 像底点photoplan 像片平面图photo rectification 像片纠正photo scale 像片比例尺phototheodolite 摄影经纬仪physiological parallax 生理视差picture format 像幅pinhole 小孔(成像)pixel 像元planarity 平面性、平面条件platform 平台platen 压平板、平台plot 平面图、略图plumb line 铅垂线point marking 刺点point transfer 转点point of interest 兴趣点polar 极、极地的polar coordinates 极坐标polarized 极化polarization 极化polygon 多边形polynomial 多项式positive 正片power spectrum 功率谱precision 精密度precision estimation 精度估计prediction 预测、推估prick point 刺点primary color 原色principal component transformation 主分量变换principal distance of photo 像片主距principal distance 主距principal line 像主纵线principal plane 像主垂面principal point 像主点principal point of photograph 像主点principle of geometric reverse几何反转原理printer 印相机prism 棱镜precision estimation 精度估计probable error 或然误差probability 概率论processing 处理bulk processing 粗处理precision processing 精处理product 产品production 生产、产量projection 投影projection center 投影中心projection printing 投影晒印propagation of errors 误差传播protocol 协议prototype 原型pseudo-color image 伪彩色影像pseudo range measurement 伪距测量pushbroom imaging 推扫式成像pyramids 金字塔Qquadtree 四叉树qualitative 定性的quality control 质量控制quantitative 定量的quantizing 量化quantization 量化quantum 量子query 查询、检索Rradargrammetry 雷达图象测量radial distortion 径向畸变radial triangulation 辐射三角测量radiant 辐射的radiation correction 辐射校正radiograph X光照相radiometry 辐射测量radiometric correction 辐射校正radiometer 辐射计random error 随机误差、偶然误差random variable 随机变量raster grid 栅格网raster to vector conversion栅格-矢量转换ratio transformation 比值变换real-aperture radar 真实空径雷达real-time photogrammetry实时摄影测量reconstruction 重建rectifier 纠正仪rectification 纠正affine rectification 仿射纠正reduction 归化redundancy 余redundant information 余信息refinement 改正reflectance spectrum 反射波谱region of target 目标区region of search 搜索区relative flying height 相对航高relative orientation 相对定向relaxation 松池reliability 可靠性relief displacement 投影差resampling 重采样remote sensing 遥感aerial remote sensing 航空遥感space remote sensing 航天遥感remote sensing of resources 资源遥感environmental remote sensing环境遥感geological remote sensing 地质遥感ocean remote sensing 海洋遥感forest remote sensing 森林遥感atmospheric remote sensing大气遥感infrared remote sensing 红外遥感microwave remote sensing 微波遥感multi-spectral remote sensing多光谱遥感active remote sensing 主动遥感passive remote sensing 被动遥感remote sensing platform 遥感平台representation 显示、表达reseaux 网格resection 后方交会residual 残差resolution 分解力、分辨率ground resolution 地面分解力space resolution 空间分辨率temporal resolution 时间分辨率temperature resolution 温度分辨率resolving power of lens 物镜分辨力restitution 测图、成图、复原、恢复restoration 恢复retrieval 检索return beam vidicon camera反束光导(RBV)管摄影机reversal film 反转片roam 漫游rotation matrix 旋转矩阵route 路径Ssampling 采样sampling interval 采样间隔satellite altimetry 卫星测高satellite attitude 卫星姿态satellite-borne sensor 星载遥感器saturation 饱和度scaling of model 模型缩放scanner 扫描仪searching area 搜索区seasat 海洋卫星segmentation 分割self-calibration 自检校semiconductor 半导体semi-metric camera 半量测摄影机sensitivity 感光度sensitometry 感光测定sensitization 感光sensitometry 感光度测定sensitive material 感光材料sensor 传感器sequential 序列的shadow 阴影shutter 快门sidelap 旁向重叠side-looking radar侧视雷达(SLR)similarity 相似、相似性simulation 模拟single image 单张像片singularity 奇异性small format aerial photography小像幅摄影space intersection 空间前方交会space photography 航天摄影space photogrammetry航天摄影测量space remote sensing 航天遥感space resection 空间后方交会Spacelab 空间实验室space shuttle 航天飞机spatial 空间的spatial domain 空间域specification 规范、说明spectral 光谱的spectral sensitivity 光谱感光度spectrograph 摄谱仪spectrometer 波谱测定仪spectroradiometer 光谱辐射仪spectrum character curve波谱特征曲线spectrum response curve波谱响应曲线spectrum feature space 波谱特征空间sphere 球面、球体spline 样条squint 斜视static 静态的stellar camera 恒星摄影机standard deviation 标准差standard error 标准差statistical 统计的statoscope 高差仪stereocamera 立体摄影机stereocomparator 立体坐标量测仪stereometer 立体量测仪stereo pair 立体像对stereo plotter 立体测图仪stereoscope 立体镜bridge-type ~ 桥式立体镜mirror ~ 反光立体镜stereoscopic vision 立体视觉stereoscopic observation 立体观测stereopair 立体像对stereophotogrammetry立体摄影测量stereoscopic model 立体观测模型stop-number 光圈号数stochastic 随机的strips 航线、航带strip aerial triangulation航带法空中三角测量sub pixel 子像素sun-synchronous satellite太阳同步卫星superimposition 叠加supervised classification 监督分类surface model 表面模型survey adjustment 测量平差survey mark 测量标志surveying and mapping 测绘surveying 测量学elementary surveying 普通测量topographic survey 地形测量control surveying 控制测量sweep 扫描swing angle 像片旋角(yaw)symmetry 对称synthetic aperture radar合成空径雷达system integration 系统集成systematic error 系统误差Ttangential distortion 切向畸变target area 目标区template 模板terrestrial camera 地面摄影机terrestrial photogrammetry地面摄影测量texture enhancement 纹理增强texture analysis 纹理分析thematic map 专题地图thematic mapper 专题制图仪(TM)theodolite 经纬仪thermal radiation 热辐射thermal infrared imagery 热红外影像threshold 阈值tie point 连接点tilt angle of photograph 像片倾角tilt displacement 倾斜位移tracing 跟踪transparent negative 透明负片transparent positive 透明正片triangulated irregular network不规则三角网(TIN)triple 三倍的、三重的true-orthophoto 真正射影像two-medium photogrammetry toning 调色topographic map 地形图topology 拓扑toponomastics, toponymy 地名学trainning field 训练区transmittance 透光率translation 平移、移动transparent 透明的transverse 横轴、横向的triangulation 三角测量aerial ~ 空中三角测量analogue aerial ~ 模拟法空三测量analytical aerial ~ 解析法空三测量block ~ 区域网空中三角测量strip ~ 航带法空中三角测量independent model ~独立模型法空中三角测量bundle ~ 光束法空中三角测量trichromatic 三色的Uuncertainty 不确定性underwater camera 水下摄影机under photogrammetry水下摄影测量universal method of photogrammetric unit matrix 单位矩阵unit weight 单位权unsupervised classification非监督分类update 更新urban mapping 城市制图user interface 用户界面mapping 全能法测图Vvanishing point 灭点、合点variance 方差variance-covariance 方差-协方差vectograph method of stereoscopic viewing 偏振光立体观察vector 矢量vectorization 矢量化verifiability 置信度verification 确认vertical 竖直的、高程的vertical exaggeration 高程扩张vertical parallax上下视差(y-parallax)vertical photography 竖直摄影viewpoint 视点virtual reality 虚拟现实visual 目视的visual interpretation 目视判读visualization 可视化voxel 体素Wwavelet 小波wavelength 波长weight 权weight function 权函数weight matrix 权矩阵weighted mean 加权平均数whiskbroom 横扫式workstation 工作站XX-ray photogrammetry X射线摄影测量Yyan angle 航偏角y-tilt 航向倾角Zzenith angle 天顶角zonal rectification 分带纠正zone 带zone generation 区域增长zoom 缩放zoom in 缩小zoom out 放大注:更详细的摄影测量与遥感专业词汇请查阅:1、《英汉测绘词汇》. 测绘出版社2、《测绘学名词》. 测绘出版社, 2002缩写词CAC Computer-aided Cartography 机助地图制图CCD Charge-coupled Device 电荷偶合器件DCBD Digital Cadastral Database 数字地籍数据库DLG Digital Line Graph 数字线划图DRG Digital Raster Graphics 数字栅格图DOQ Digital Orthophoto Quadrangle 数字正射影像图DPW Digital Photogrammetric Workstation摄影测量工作站GLONASS Global Orbiting Navigation Satellite System [俄罗斯]全球轨道导航卫星系统GPS Global Positioning System 全球定位系统ERTS earth resources technology satellite 地球资源卫星ETM Enhancement Thermatic Mapper 增强型专题制图仪HRSC High Resolution Stereo CameraIFOV Instantaneous Field of View 瞬时视场IFSAR Interometry SAR干涉雷达IMU Inertial Measurement Unit 惯性测量装置INS Inertial Navigation System 惯性导航系统ISS Inertial Surveying System 惯性测量系统LIDAR Light Detection and Ranging 激光探测和测距LIS Land Information System 土地信息系统MTF Modulation Transfer Function 调制传递函数NDVI Normalized Difference Vegetative IndexNSDI National Spatial Data Infrastructure 国家空间数据基础设施RMSE root mean square error 均方根差,中误差SAR Synthetic Aperture Radar 合成空径雷达SDI Spatial Data Infrastructure 空间数据基础设施SLAR Side Looking Airborne Radar 侧视雷达WGS84 World Geodetic System for 1984 1984年世界大地坐标系学会、组织名称ACSM American Congress on Surveying and Mapping 美国测绘学会ASPRS American Society for Photogrammetry and Remote Sensing美国摄影测量与遥感学会CSGPC Chinese Society of Geodesy, Photogrammetry and Cartography 中国测绘学会ESA European Space Agency 欧洲空间局FIG Federation International of Geometres 国际测量师联合会ICA International Cartographic Association 国际制图协会ISO International Organization for Standardization 国际标准化组织ISPRS International Society for Photogrammetry and Remote Sensing国际摄影测量与遥感学会IUSM International Union of Surveying and Mapping 国际测量联合会NASA National Aeronautics and Space Administration [美国]国家航空与航天局NASDA National Space Development Agency [日本]国家宇宙开发事业团NGCC National Geomatics Center of China [中国]国家基础地理信息中心。
多波束测深声纳的后处理流程1.首先,对接收到的声纳信号进行滤波处理,去除噪声干扰。
Firstly, the received sonar signals should be filtered to remove noise interference.2.然后,对滤波后的信号进行时频分析,提取深度信息。
Then, the filtered signals should be subjected to time-frequency analysis to extract depth information.3.接下来,利用多波束技术,将声纳信号分成多个波束。
Next, using multi-beam technology, the sonar signals should be divided into multiple beams.4.同时,对每个波束进行幅度和相位补偿,确保准确的深度测量。
Simultaneously, amplitude and phase compensation shouldbe applied to each beam to ensure accurate depth measurement.5.然后,将各个波束的深度测量结果进行融合,得到最终的测深结果。
After that, the depth measurement results from each beam should be fused to obtain the final depth measurement result.6.对融合后的深度结果进行统计分析,评估深度测量的精度和稳定性。
Statistical analysis should be applied to the fused depth results to evaluate the accuracy and stability of depth measurement.7.最后,生成深度剖面图和三维地形模型,以便进行后续的数据分析和应用。
一种高分辨率3维图像的自适应降噪算法向志聪;张程潇;白玉磊;赖文敬;王钦若;周延周【摘要】为了获得高保真3维图像,采用了一种针对高分辨率3维图像的自适应均值降噪算法。
首先使用一种由激光器、高分辨率3维相机、直线电机和计算机等设备组成的线激光高精度3维测量实验系统对自然纹理皮革进行测量。
然后针对系统测量所得的高分辨率3维自然纹理图像(每英寸点数大于1000),进行了理论分析和实验验证,取得了降噪后的高保真3维图像数据,并与传统的均值滤波、小波变换滤波的降噪效果进行对比。
结果表明,该算法能自动选取最优的降噪窗口,有效地去除3维图像的噪声信息,并保留高分辨率图像丰富的边缘、细节信息,最终得到高保真的高分辨率3维自然纹理图像。
该实验结果对于高分辨率图像的降噪问题是十分有帮助的。
%In order to obtain high-fidelity 3-D images, an adaptive mean filtering algorithm for high resolution 3-D images was proposed.Firstly, a high-precision 3-D linear laser measuring system consisting of a laser , two high-resolution 3-D cameras, two linear motors and a computer was established to measure the texture of leather .After theoretical analysis and experimental verification of the high-resolution 3-D texture images ( dots per inch>1000) collected by the measuring system , the data of high-fidelity three dimensional images after filtering were gotten .The effect of the adaptive mean filtering algorithm was compared with the effects of mean filtering method and wavelet threshold filtering method .The results show that the adaptive mean filtering algorithm can remove noise of 3-D images effectively , select the appropriate filtering window automatically , and also keepdetails and edge information of high resolution images .Finally, the high resolution 3-D texture images with high fidelity would be obtained.The experimental results are very helpful for denoising processing of high resolution images .【期刊名称】《激光技术》【年(卷),期】2015(000)005【总页数】5页(P697-701)【关键词】图像处理;高保真3维图像;自适应均值降噪;高分辨率;线激光;3维测量【作者】向志聪;张程潇;白玉磊;赖文敬;王钦若;周延周【作者单位】广东工业大学自动化学院,广州510006;广东工业大学自动化学院,广州510006;广东工业大学自动化学院,广州510006;广东工业大学自动化学院,广州510006;广东工业大学自动化学院,广州510006;广东工业大学自动化学院,广州510006【正文语种】中文【中图分类】TP391.41引言随着激光机器视觉技术在工业生产中的迅速发展,在3维自然纹理[1-2]立体印刷方面,物体表面3维轮廓测量技术应用广泛。
2013 年 10 月 第 6 卷 第 5 期 中国光学 Chinese Optics Vol. 6 No. 5 Oct. 2013文章编号 1674-2915(2013)05-0701-09星载微光立体成像技术及实现胡晓华 ∗ ,周晓中,刘松涛,张春华,杨 楠( 中国人民解放军 61741 部队,北京 100094 )摘要:为了监测夜间和晨昏时段的低云大雾,实现云的三维立体成像,对微光立体成像的关键技术进行了研究。
首先, 介 绍了微光立体成像原理,分析了成像需要解决的宽视场覆盖和多镜头布局。
然后,介绍了实现微光探测需要解决的低照 度成像技术及其实现方法。
最后 ,针对观测目标照度变化较大的问题, 提出了动态范围拓展技术, 介绍了后期数据处理 中的云雾监测技术。
仿真计算结果表明:采用电子倍增 CCD( EMCCD) 探测器和推扫扫描成像模式 、 集成探测器组件以 及多台相机拼接方案可有效实现微光立体成像,相机扫描幅宽超过 2 800 km; 高程分辨率 < 817. 7 m。
提出的成像技术 可在低照度条件下监测低云大雾,获取高分辨率的三维立体云图,满足气象海洋探测的需求。
关 键 词 :微光立体成像;低照度成像;低云大雾;立体云图 中图分类号 :TP73 文献标识码:A doi:10. 3788 / CO. 20130605. 0701Spaceborne shimmer tridimensional imaging technology and its implementationHU Xiao-hua ∗ , ZHOU Xiao-zhong, LIU Song-tao, ZHANG Chun-hua, YANG Nan ( No. 61741 Troop ,the Chinese People′s Liberation Army,Beijing 100094,China) ∗Corresponding author, E-mail:x. h. hu @ 163 . commensional imaging of the clouds, the key technologies of shimmer tridimensional imaging were discussed.Abstract : In order to detect low clouds and heavy fogs during nighttime and twilight, and to achieve three-diFirst, the theory of shimmer tridimensional imaging was introduced, and the wide-field coverage and multi-lens layout for imaging were analyzed. Then, the low-light imaging technology and its implementation were introtechnology is presented, and detecting technology for clouds and fogs was introduced. Emulation calculation results indicate that the EMCCD detector and push-broom imaging mode, integrated detector assembly and the multi-camera stitching program can effectively realize shimmer tridimensional imaging. The camera swath is beyond 2 800 km and elevation resolution is less than 817. 7 m. By using this imaging technology, we can de-duced. Finally, aiming at the larger illuminance change of an observed target, the dynamic range expandingtect the low clouds and heavy fogs in a low-light condition, and can get high-resolution three-dimensional imaging of the clouds, which satisfies the requirements of meteorologycal and oceanic detection. image Key words: shimmer tridimensional imaging;low-light imaging;low cloud and heavy fog;tridimensional cloud 收稿日期:2013-07-13 ;修订日期:2013-09-16 基金项目:国家自然科学基金资助项目( No. 41205004)702 中国光学 第 6 卷 1 引 言 低云大雾天气多产生于夜间和晨昏时段, 是 造成低能见度的主要天气现象,严重影响航海、航 空、公路运输安全[1]表目标进行推扫,可获取月表同一目标星下点、前 视 16. 7°、后视 16. 7° 3 幅二维原始数据图像, 经 辐射定标后重构月表三维立体影像。
Improved resolution three-dimensional integral imaging using optimized irregularlens-array structureZahra Kavehvash,1,*Khashayar Mehrany,1and Saeed Bagheri21Department of Electrical Engineering,Sharif University of Technology,P.O.Box11365-8639,Tehran,Iran 2Philips Research North America,345Scarborough Road,Briarcliff Manor,New York10510,USA*Corresponding author:zkavehvash@Received29May2012;revised26July2012;accepted26July2012;posted26July2012(Doc.ID169490);published24August2012A rigorous approach is proposed to improve the resolution of integral imaging(InI)by finding the appro-priate form of irregularity in the arrangement of the InI lenslets.The improvement of the resolution isachieved through redistribution of the sampling points in a uniform manner.The optimization process forfinding the optimum pattern of the lens-array irregularity is carried out by minimizing a cost function,whose mathematical closed-form expression is provided.The minimization of the proposed cost functionensures the uniform distribution of sampling points and thus improves the resolution within the desireddepth of field(DOF)and field of view(FOV).A set of standard resolution charts is used to demonstratethe improvement of the quality of the three-dimensional(3D)images obtained by using the optimizedirregular lens array.It is shown that the overall level of the lateral and depth resolutions is improved atthe same time.©2012Optical Society of AmericaOCIS codes:110.6880,110.3000.1.IntroductionThree-dimensional(3D)integral imaging(InI)does not require wearing special eyeglasses to provide autostereoscopic images from a continuous view-point[1–6]and thus counts among the promising 3D imaging methods to be used for commercial3D visualization.Although more than a century-old technique[1],it has recently attracted increasing at-tention thanks to the renewed interest in3D imaging [7].A conventional InI system captures the visual in-formation of a3D object through a regular flat lens array and forms a bunch of elemental images(EIs). Since each EI provides a different perspective of the 3D object,the original3D object is reconstructed once the EIs are displayed on an optical device placed in front of a similar lens array.Despite the many-sided advantages brought by using the InI system,the reconstructed3D images have limited depth of field(DOF)and field of view (FOV)together with a low level of lateral and depth resolution.Many researches have been conducted to improve InI by adding different sorts of irregularity to the conventionally used flat lens array having si-milar lenslets.DOF improvement is already reported when curved lens arrays[8],and flat lens arrays made of lenslets with different focal lengths are em-ployed for InI[9].FOV improvement is also reported when appropriately curved lens arrays are used [10–12].The possibility of achieving a higher level of depth and lateral resolution by finding and adding the proper form of irregularity is,however,not a very well-studied subject.Such a study necessitates a quantitative gauge to measure the level of achiev-able lateral and depth resolution in InI systems. This has not been possible until very recently,when object-independent models based on the concept of1559-128X/12/256031-07$15.00/0©2012Optical Society of America1September2012/Vol.51,No.25/APPLIED OPTICS6031sampling rays were introduced to quantify the lateral and depth resolution[13].A sampling ray connects the center of each pixel on the display de-vice to the center of the corresponding lens in the lens array and thus carries the information necessary for image reconstruction[13–15].The intersection point of each sampling ray and the image plane is referred to as the sampling point[13].Given that two or even more sampling rays can intersect with each other at a specific image plane,the concept of the order of the sampling points was introduced to enumerate the in-tersecting sampling rays.The n th-order sampling point was thus defined to designate the intersection of n 1sampling rays.In the most recent work on the subject,the total number of the first-order sam-pling points is related to the lateral resolution of the InI system while the depth resolvability of different points of the image domain is related to the order of its sampling point[13].In this fashion,the depth and lateral resolution of the InI system is measured and a mathematical cost function is proposed to find the appropriate irregular pattern of the lens array that improves both lateral and depth resolvability in the desired DOF and FOV range.This is,to the best of our knowledge,the first attempt to propose a rigorous approach for finding the optimum irregu-lar pattern achieving higher depth and lateral resolution.The structure of this paper is as follows:we first introduce the overall structure of an irregular lens array,extract the coordinates of the k th-order sam-pling points,and optimize the structure to ensure a more uniform distribution of sampling points—all in Section2.We then present the simulation results in Section3and thus confirm the claimed improvement observed in the quality of the images reconstructed by using the optimized irregular lens array.Finally,we make the conclusions in Section4.2.Optimized Irregular Lens-Array PatternIt is already shown that the distribution of the sampling points is rather nonuniform whenever con-ventional flat lens arrays made of similar lenslets are employed[13].Quite often,the sampling points get accumulated at specific image planes.Since the high-er density of sampling points warrants a higher lat-eral resolution,any such plane is referred to as the lateral resolution plane.Likewise,a lower number of higher-order sampling points occasionally pile up at some other image planes.Since the presence of higher-order sampling points ensures a good depth resolvability,this latter type of planes is referred to as the depth resolution plane.Given that the high-order sampling points are formed by the inter-section of more sampling rays,there is a trade-off be-tween the number and order of sampling points at each lateral image plane and thus the good lateral resolution in the lateral resolution planes is bought at the expense of the depth resolvability[10].It is therefore conceivable that the uniform distribution of sampling points would be very much desired. Therefore,we are trying to rearrange the samplingrays in such a manner that the sampling pointsof different orders become uniformly distributed within the imaging space.This can be achieved byintroduction of a meticulous irregularity in the posi-tion and direction of the lenslets in the lens-array structure.Using the Cartesian coordinate system,it is hereassumed that the3D objects are to be reconstructedwithin a specific region lying between z z1,z z2, x x1,x x2,y y1,and y y2.This specific regionis hereafter referred to as the region of interest(RoI).It is within the RoI that the distribution of thespatial coordinates of the sampling points and their orders is tried to be made uniform.First,a conven-tional regular lens array is made irregular to showthat the distribution of the sampling points of differ-ent orders can be controlled.Then,the coordinates ofthe n th-order sampling points lying within the RoIare extracted in terms of the position and direction of the lenslets in a lens array with arbitrary irregu-larity.The appropriate cost function to be used foroptimizing the irregular pattern of the lenslets is finally introduced.A.Irregular Lens-Array StructureAn irregular lens array with an arbitrary pattern is schematically shown in Fig.1.Three different crosssections of the structure in the xy,yz,and xz planes(front view,top view,and left view)are shown in Figs.1(a),1(b),and1(c),respectively.Assuming thatthe original flat lens array was originally placed inthe xy plane,the p,q th lenslet of the array is shifted along the z-axis by s pq,and rotated byθx;pq andθy;pqaround the x-and y-axes,respectively.Insofar as thesampling ray connects an arbitrary input pixel of a specific EI,viz.P1in Figs.1(b)and1(c),to the centerof its corresponding lens,the irregularity of thelenslets—controlled by s pq,θx;pq,andθy;pq—affects the spatial arrangements of the sampling rays.Thisis clearly demonstrated in Figs.1(b)and1(c),wherethe sampling rays of the input pixel P1in the regular and irregular lens arrays are plotted by dashed andsolid lines,respectively.Once the sampling rays arerearranged by changing s pq,θx;pq,andθy;pq,the popu-lation of the sampling points of different orders is controlled within the RoI.This point is further expounded below,where the coordinates of the n th-order sampling points are extracted.B.Extraction of the n th-Order Sampling PointsThe coordinates of all sampling points can be easilyextracted once the algebraic equation of each sam-pling ray emanating from the i,j th pixel of the p;q th EI is given.Since each sampling ray passes through the center of its corresponding lenslet in the array,the governing equation of a typical sam-pling ray can be written in terms of its pixel co-ordinates x i;y j;−g ,and its lenslet coordinates x p;y q;s pq :6032APPLIED OPTICS/Vol.51,No.25/1September2012z g s pq x −x ix p i y −y j y q j.(1)Here,g is the distance between the display device and the lens-array plane.It should be pointed out that the sampling ray passing through the p;q th lenslet lies within the FOV of the lenslet:αx and αy along the x and y directions,respectively.Therefore,the following two relations are held:tan −1x p −x ig−θx;pq ≤αx tan −1y q −y jg−θy;pq ≤αy .(2)Similarly,the length of the sampling ray is limitedto the DOF of the lenslet lying between z L and z R in the regular lens array.Therefore,the z -coordinate of the sampling ray in the irregular structure is subjected to the following relation:z a − z a −z L cos θx;pq cos θy;pq s pq <z <z az R −z a cos θx;pq cos θy;pq s pq ;(3)where z a is the focused image plane satisfying the lens law .The coordinates of the zeroth-order sampling points at the image plane z i can then be obtained straightforwardly:8>><>>:z z i x z i g x p −x i s pq g x i y z i g y q −y j s pq gyj; 4where z i fulfills the preceding inequality givenby Eq.(3).The coordinates of the higher-order sampling points are not very easy to extract.It requires solving a set of linear equations.The coordinates of the first-order sampling points are extracted by finding the intersection point of two different sampling rays,each one emanated from a different EI.The coordi-nates of the first-order sampling points satisfy the following set of equations:8>><>>:x −x ix p −x i x −x i 0x p 0−x i 0y −y jq −y j y −y j 0q 0−y j 0x p −x i pq g z g x i x p 0−x i 0pq gz g x i 0; 5where p;q ≠p 0;q 0to make sure that the sampling rays are coming from different EIs (sampling rays coming from the same EI does not cross with each other).Once again,the z -coordinate of the intersec-tion point should fulfill the DOF inequality given in Eq.(3).Along the same line,the coordinates of the n th-order sampling points are expected to beextractedFig.1.Regular and irregular lens arrays,their typical sampling rays,and the RoI.Lenslets of the regular and irregular lens arrays and their sampling rays are depicted by dashed and solid lines,respectively in (a)front view ,(b)top view ,and (c)left view .1September 2012/Vol.51,No.25/APPLIED OPTICS6033by finding the intersection point of n 1 samplingrays.It therefore seems that the unknown x-,y-,and z-coordinates of the intersection point should fulfill aset of3n equations.That would leave us with an over-determined set of linear equations.It should,how-ever,be noted that each sampling ray is in real fact a beam of nonzero width and thus the n th-order sampling point is formed not only when n 1 sam-pling rays are crossing each other but also when they are in the vicinity of each other.Therefore,a certainlevel of error can be tolerated in the fulfillment of the 3n equations governed by the intersection of n 1 sampling rays.The three unknown coordinates of the n th-order sampling point are thus extracted by find-ing those specific coordinates whose overall error in satisfaction of the overdetermined set of3n equa-tions is below a certain threshold level.This can be done by following a standard optimization algo-rithm.Once more,the coordinates of the n th-order sampling points are subjected to the DOF inequality expressed in Eq.(3).C.Optimization ProcessNow that the coordinates of the n th-order sampling points are at hand,an appropriate cost function is needed to find the optimum irregular pattern of the lenslets.The appropriate cost function is ex-pected to reach its minimum value when s pq,θx;pq, andθy;pq of each lenslet result in a uniform distribu-tion of all those sampling points that are lying within the RoI.It is therefore necessary to have a mathema-tical expression to quantify the uniformity of the sampling point distribution.The first step toward this end is the measurement of the distance between the neighboring sampling points whose coordinates lie within the RoI cube.Here,the Delaunay triangu-lation algorithm is employed[16].Once the Delau-nay triangles are generated,the length of sides of the Delaunay triangles are recorded in a vector whose average and variance are denoted by E dandσ2d ,respectively.Insofar as higher E d,andσ2dim-plies a lower level of uniformity in the distribution of the sampling points,the proposed cost function is setproportional to E d andσ2d .Given that the minimization of E d andσ2d does notensure that the total volume of the RoI is uniformly covered,the marginal sampling points whose x-,y-, and z-coordinates are close enough to the border of the RoI are further studied.These marginal sam-pling points are selected by pursuing the following algorithm.The first k sampling points whose x-coordinates are closest to x1,the first k sampling points whose y-coordinates are closest to y1,and the first k sampling points whose z-coordinates are closest to z1are all selected.Similarly,The first k sampling points whose x-coordinates are closest to x2,the first k sampling points whose y-coordinates are closest to y2,and the first k sampling points whose z-coordinates are closest to z2are also se-lected.They are hereafter referred to as the marginal sampling points.The average of the distance between different marginal sampling points and the borders of the RoI is calculated together with its variance.They are denoted by E m andσ2m Along the same line,E m andσ2m are expected to be as low as possible in the optimized irregular lens array. Finally,to ensure that not only the sampling points but also their order are uniformly distributed,the frequency of observing the n th-order sampling points should be studied.Assuming that C n denotes the to-tal number of the n th-order sampling points that can be counted within the RoI,it is desired to have al-most equal C n s.Given that equal C n s maximize ΣC2n whenever there are N sampling points,the pro-posed cost function is set to be inversely proportional toΣC2n.It is therefore written as follows:f s pq;θx;pq;θy;pqE2dσ2dE2m σ2mN ΣC2n.(6)Decreasing the first and second terms in the nu-merator of the proposed cost function guarantees the constellation of the sampling points in the vici-nity of each other,and the proximity of them to the borders of the RoI,respectively.Increasing the denominator of the cost function,on the other hand, ensures the uniformity of the distribution of the or-der of the sampling points.Therefore,the optimum s pq,θx;pq,andθy;pq minimize the proposed cost func-tion.It should,however,be kept in mind that there are some constraints imposed on the dynamic range of s pq,θx;pq,andθy;pq.These constraints should be ap-plied when the optimization algorithm is running to minimize the cost function.3.Simulations and AnalysisIn this section,a typical imaging system with a reg-ular lens array is considered.It is composed of21×21similar lenslets.The lens pitch is5mm.Assuming that the distance between the display device and the lens array is g 50mm,and that each EI gets25×25pixels of the display device,there are2060sam-pling points within the RoI,100×100×200mm3. Using the Delaunay triangulation algorithm,it can be shown that Ed 0.77mm andσ2d0.05mm2 for the sampling points.It can be also shown that E m 0.61mm andσ2m 0.1mm2for the marginal sampling points.Furthermore,there are C1 1648,C2 232,C3 60,C4 50,C5 0,C6 40, and C7 30sampling points of the first,second, third,fourth,fifth,sixth,and seventh orders,respec-tively.Counting the total number of first-and seventh-order sampling points at different lateral planes,the resolution and depth planes are found to be at z 400mm and z 416.7mm,respectively. The former has140first-order sampling points and the latter has30seventh-order sampling points. Using the genetic algorithm to minimize the pro-posed cost function,the optimized values of s pq,θx;pq,andθy;pq of each lenslet are found.This time, N 2436sampling points are counted within the6034APPLIED OPTICS/Vol.51,No.25/1September2012RoI and we have E d 0.71mm,σ2d 0.004mm 2,E m 0.65mm,and σ2m 0.01mm 2.Reduction ofσ2d and σ2m stands witness for the fact that the distri-bution of the sampling points is now more uniform.Growth of the total number of the sampling points is also a benefit.Even more,we have C 1 860,C 2 416,C 3 308,C 4 272,C 5 280,C 6 160,and C 7 140and thus C i s ,i 1;…7are made closer to each other.The sampling points of the optimized irregular lens array are distributed in such a uniform fashion that the lateral and depth resolution planes cannot be easily discriminated from each other.Be-fore moving further on examination of this point in detail,it is perhaps necessary to say a few words on explanation of how the EIs are to be recorded and displayed via the designed irregular lens array .Since each lenslet in the irregular lens array is pos-sibly rotated whereas the sensor behind it remains fixed,the lens-array pattern cannot be made irregu-lar by simply rotating the cameras —which would ro-tate lens and sensor both.Still,the EIs to be recorded via the irregular structure can be easily obtained by computational processing of the EIs recorded via the regular structure.This computational process takes advantage from two essential facts.First,rotation of lenslets by θx;pq and θy;pq is equivalent to rotation of the EI plane by -θx;pq and -θy;pq .Second,axial shift of each lenslet by s pq has the same effect as does changing the focal length of each lenslet to f pq :f pq1f 1g −1g s pq−1.(7)Here,the standard computational recording pro-cess [17]is pursued to obtain every p;q th EI.The thus obtained EIs are then postprocessed and the EIs that would be recorded by the irregular struc-ture are obtained.Similarly,the reconstruction stage is performed computationally .It is,however,worth noting that these EIs are also usable in physical re-construction of the 3D scene if one employs spatial-light-modulator to mimic the irregular lens-array pattern [18].Now ,as a demonstrative example,two resolution charts are placed at the lateral and depth resolution planes of the original regular lens array at z 400mm,and z 416.7mm,respectively .The former is hereafter referred to as the plane A ,and the latter as the plane B .The original scene com-posed of these two resolution charts placed at two dif-ferent planes is then reconstructed at the plane A .The reconstructed images of the regular and irregu-lar lens arrays are shown in Figs.2(a)and 2(c),re-spectively.Although the resolution chart placed at the plane B is not expected to be observed when the scene is reconstructed at the plane A ,it imprints a conspicuous shadow because the lateral and depth resolution planes are close to each other.This un-wanted shadow is,however,very strong when the scene is reconstructed by using a regular lens arraysince the good lateral resolution at plane A is actu-ally bought at the expense of the depth resolvability.Figure 2(c)demonstrates that the unwanted effect caused by the shadow of the resolution chart at plane B is partly rectified by introduction of appropriate ir-regularity in the lens array .This means better depth resolvability at the plane A .It should,however,be pointed out that the improved depth resolvability has its own expense as the reconstructed image of the resolution chart at plane A has lost some of its high-frequency contents when it is reconstructed by the irregular lens array .To better demonstrate this fact,the high-frequency contents of the resolu-tion charts;which are marked in Figs.2(a)and 2(c),are enlarged and shown in Figs.2(b)and 2(d).Along the same line,the scene is reconstructed as it is seen at the plane B .Figures 3(a)and 3(c)show the image reconstructed via the regular and the op-timized irregular lens arrays,respectively .This time the resolution chart placed at the plane A is not ex-pected to be observed.Given that the image recon-struction through the regular lens array enjoys the highest level of depth resolvability at the plane B ,the unwanted shadow of the resolution chart placed at the plane A is quite weak.This is not true for the irregular lens array because the sampling points are uniformly distributed and there are neitherdepthFig.2.(Color online)(a)Reconstructed image in the lateral reso-lution plane (plane A )of regular lens array ,(b)its high-frequency contents enlarged to show how good the resolution is,(c)recon-structed image in the lateral resolution plane (plane A )of irregular lens array ,and (d)its high-frequency contents enlarged to show how good the resolution is.1September 2012/Vol.51,No.25/APPLIED OPTICS6035nor resolution planes.Rather,the reconstructed images have almost equal quality when they are re-constructed at different planes.It is worth noting that even though the unwanted shadow is a bit stron-ger for the irregular lens array when the scene is re-constructed at the plane B ,the lateral resolution achieved by the irregular lens array is better than the lateral resolution achieved by the regular lens array.Once again,the high-frequency contents of the resolution charts,which are marked in Figs.2(a)and 2(c),are enlarged and shown in Figs.2(b)and 2(d).Finally,a third resolution chart is added to the original scene.It is placed at z 408.2mm.This plane —which is here after referred to as the plane C —has no non-zeroth-order sampling points and thus has inferior resolution.The scene is now recon-structed at the plane C and the image obtained by the regular and irregular lens array is shown in Figs.4(a)and 4(c),respectively .The poor quality of the reconstructed image is readily noticeable in Fig.4(a),showing the image reconstructed by the regular lens array .The shadows of the resolution charts placed at the planes A and B are conspicuous,and the resolution chart at the plane C has low qual-ity [Fig.4(b)].Thanks to the uniform distribution of the sampling points in the RoI of the optimized irregular lens array ,the poor quality of image recon-struction at the plane C is partly boosted.The unwanted shadows are weaker in Fig.4(c),and thelateral resolution is higher,when the optimized irre-gular lens array is used for image reconstruction.This is clarified in Figs.4(b)and 4(d),where the high-frequency contents of the resolution charts are magnified.All these figures stand witness for the fact that the sampling points in the optimized irregular lens array are rearranged uniformly.There are no lateral reso-lution planes with bad depth resolvability and no depth resolution planes with bad lateral resolution.Rather,a same good level of depth and lateral reso-lution is achieved at all different points.The mini-mum level of the lateral and depth resolution achieved by regular flat lens arrays is therefore in-creased by using the optimized irregular lens array because almost all points enjoy the same level of lat-eral and depth resolution.4.ConclusionThe idea of using irregularity in InI systems,e.g.,using curved or nonuniform lens arrays,is not un-known and has successfully improved the DOF or FOV [8–12].The possibility of using irregularity in InI systems to enhance the lateral and depth resolu-tion was,however,left to be explored.Exploration of the effects of irregularity on the resolution is just made possible thanks to theobject-independentFig.3.(Color online)(a)Reconstructed image in the depth reso-lution plane (plane B )of regular lens array ,(b)its high-frequency contents enlarged to show how good the resolution is,(c)recon-structed image in the depth resolution plane (plane B )of irregular lens array ,and (d)its high-frequency contents enlarged to show how good the resolutionis.Fig.4.(Color online)(a)Reconstructed image in z 408.2mm (plane C )of regular lens array ,(b)its high-frequency contents en-larged to show how good the resolution is,(c)reconstructed image in plane C of irregular lens array ,and (d)its high-frequency contents enlarged to show how good the resolution is.6036APPLIED OPTICS /Vol.51,No.25/1September 2012approach recently proposed to quantify the lateral and depth resolution of InI[13].This approach is in this manuscript followed to first measure the lat-eral and depth resolution of InI and then to find the optimum pattern of irregularity to increase the mini-mum achievable level of resolution.A mathematical cost function is proposed to fulfill this puta-tional InI is carried out and a typical3D scene—formed by resolution charts placed at different planes—is reconstructed.It is shown that the opti-mized irregular lens array found by using the proposed optimization algorithm achieves a higher level of resolution than the typical flat lens array con-ventionally used for InI.References1.M.G.Lippmann,“Epreuves reversibles donnant la sensationdu relief,”J.Phys.(Paris)7,821–825(1908).2.H.E.Ives,“Optical properties of a Lippmann lenticulatedsheet,”J.Opt.Soc.Am.21,171–176(1931).3.N.A.Valyus,Stereoscopy(Focal,1966).4.R.L.de Montebello,“Wide angle integral-photography:theintegram technique,”Proc.SPIE120,73–91(1970).5.T.Okoshi,Three Dimensional Imaging Techniques(Academic,1976).6.Y.A.Dudnikov,B.K.Rozhkov,and E.N.Antipova,“Obtaininga portrait of a person by the integral photography method,”Sov.J.Opt.Technol.47,562–563(1980).7.J.Y.Son,B.Javidi,and K.-D.Kwack,“Methods for displaying3D images,”Proc.IEEE94,502–523(2006).8.J.S.Jang and B.Javidi,“Depth and lateral size control ofthree-dimensional images in projection integral imaging,”Opt.Express12,3778–3790(2004).9.J.S.Jang and B.Javidi,“Large depth-of-focus time-multiplexed three-dimensional integral imaging by use of lenslets with non-uniform focal lengths and aperture sizes,”Opt.Lett.28,1924–1926(2003).10.J.S.Jang and B.Javidi,“Very-large scale integral imaging(VLSII)for3D display,”Opt.Eng.44,014001(2005).11.Y.Kim,J.-H.Park,H.Choi,S.Jung,S.-W.Min,and B.Lee,“Viewing-angle-enhanced integral imaging system using a curved lens array,”Opt.Express12,421–429(2004).12.Y.Kim,J.-H.Park,S.-W.Min,S.Jung,H.Choi,and B.Lee,“Wide-viewing-angle integral three-dimensional imaging system by curving a screen and a lens array,”Appl.Opt.44,546–552(2005).13.Z.Kavehvash,M.M.Corral,Kh.Mehrany,S.Bagheri,G.Saavedra,and H.Navarro,“Three-dimensional resolvability in an integral imaging system,”J.Opt.Soc.Am.A29, 525–530(2012).14.R.Horisaki,Y.Nakao,T.Toyoda,K.Kagawa,Y.Masaki,andJ.Tanida,“A Compound-eye system with irregular lens-array arrangement,”Proc.SPIE7072,70720G(2008).15.Z.Kavehvash,Kh.Mehrany,and S.Bagheri,“Optimizationof the lens-array structure for performance improvement of integral imaging,”Opt.Lett.36,3993–3995(2011).16.C.B.Barber,D.P.Dobkin,and H.T.Huhdanpaa,“The Quic-khull algorithm for convex hulls,”ACM Trans.Math.Softw.22,469–483(1996).17.S.-H.Hong,J.-S.Jang,and B.Javidi,“Three-dimensionalvolumetric object reconstruction using computational integral imaging,”Opt.Express12,483–491(2004).18.A.Yontem and L.Onural,“Integral imaging using phase-onlyLCoS spatial light modulators as Fresnel lenslet arrays,”J.Opt.Soc.Am.A28,2359–2375(2011).1September2012/Vol.51,No.25/APPLIED OPTICS6037。