基于独立成分分析的高光谱图像异常检测

针对高光谱图像中背景及目标先验知识未知条件下的异常目标检测问题,提出了一种基于独立成分分析(ICA)的异常探测算法.首先估计原始数据的虚拟维(VD)以确定要分离的独立成分个数,在此基础上进行快速独立成分分析(FastICA),然后基于平均局部奇异度选择含异常信息较多的独立成分,最后使用丰度量化算法得到异常目标的丰度图像...     

螺旋锥束CT中两种解析重建算法的研究

 研究了锥束螺旋Katsevich和FDK重建算法,并对这两种算法进行比较。实验结果表明：当投影数据没有噪声的时候,FDK算法和Katsevich算法均能取得较好的效果,当对实际物体进行重建的时候,投影数据含有噪声, Katsevich算法需要对投影数据求导,而它对投影数据的噪声较敏感,重建质量有所下降。     

高分辨率405 nm激光显微成像系统研究

 研究了405 nm短波长激光作为照明光源、数值孔径0.65显微物镜组成的显微成像系统。采用该系统对CD-R及DVD-R盘片进行了显微成像,并对激光成像散斑进行了消除,同时利用CCD图像传感技术和图像采集技术对显微图像进行实时观察与存储,与卤素灯白光作为照明光源时的显微图像进行了比较。结果表明：该系统在卤素灯白光作为照明光源时对CD-R盘片信息点可清晰分辨,但对DVD-R盘片信息点的图像不可分辨;而在405 nm激光照明时信息点均可清晰分辨,系统分辨优于400 nm,明显高于普通卤素灯白光照明系统。     

基于序列图像的几何参数测量方法研究

随着测量技术的不断发展,现代工业对物体尺寸检测的准确性及快速性要求越来越高.文中提出了一种利用序列图像来测量物体几何尺寸的方法.使用数码相机获得标定模板的序列图像,通过直接线性变换(DLT)方法来标定相机内部参数,结合透镜成像的知识,对使用数码相机采集到的物体序列图像进行处理和测量,最终计算出物体的宽度和高度.实验证明...     

采用树脂透镜的掌纹图像采集光学系统设计

为了获得高分辨率、高对比度和低畸变的掌纹图像,同时实现系统的轻量化和高性价比,本文基于全反射原理,采用树脂材料设计了一款由6片镜构成双远心光路的掌纹采集光学系统。树脂材料的选用减轻了光学系统的总重量;基于光的全反射原理的系统设计增强了掌纹图像的对比度;选择双远心光学结构,便于对倾斜物面所产生的梯形畸变进行矫正。对所设计光学系统的成像质量分析表明,该系统所有视场的光学传递函数（MTF）在Nyquist频率228 lp/mm处均达0.55以上,畸变〈0.14%。设计的光学系统可以采集120 mm×160 mm的手掌区域,实际手掌面上的分辨率达到500dpi,采集的掌纹图像分辨率达到8.0×106 pixel,满足了实际采集的要求。     

光声成像技术的最新进展

光声成像技术是生物医学领域中新兴的无损检测技术,具有对比度高、分辨率好、穿透能力强等优点.本文介绍了光声成像技术近年来的进展状况,主要涉及成像探测方式的改进、成像速度的加快、成像分辨率的提高以及图像重构算法的发展等.以该项技术在现代临床诊断中的应用为例,描述了其在生物医学领域中应用范围的拓宽.最后,总结了该项技术现存的...     

Performance of third-order ghost imaging with second-order intensity correlation

The third-order ghost imaging with the second-order intensity correlation is theoretically and experimentally demonstrated.The resolution and visibility of the reconstructed image are discussed,and the relationship between resolution and visibility is analyzed.The theoretical results show that a tradeoff exists between the visibility and resolution of the reconstructed image;the better the image resolution,the worse the image visibility.Numerical simulations are carried out to verify this theory,and a ghost...     

Minimum mean square error method for stripe nonuniformity correction

Stripe nonuniformity is very typical in line infrared focal plane (IRFPA) and uncooled starring IRFPA. We develop the minimum mean square error (MMSE) method for stripe nonuniformity correction (NUC). The goal of the MMSE method is to determine the optimal NUC parameters for making the corrected image the closest to the ideal image. Moreover, this method can be achieved in one frame, making it more competitive than other scene-based NUC algorithms. We also demonstrate the calibration results of our algorithm using real and virtual infrared image sequences. The experiments verify the positive effect of our algorithm.     

Combining clustering and classification for remote-sensing images using unlabeled data

A joint clustering and classification approach is proposed.This approach exploits unlabeled data for efficient clustering,which is applied in the classification with support vector machine(SVM) in the case of small-size training samples.The proposed method requires no prior information on data labels,and yields better cluster structures.Through cluster assumption and the notions of support vectors,the most confident k cluster centers and data points near the cluster boundaries are labeled and used to train a reliable SVM classifier.Our method gains better estimation of data distributions and mitigates the unrepresentative problem of small-size training samples.The data set collected from Landsat Thematic Mapper(Landsat TM-5) validates the effectiveness of the proposed approach.     

基于窄带多区域水平集方法的遥感图像分割

由于遥感图像存在边缘混叠等问题,经典的C-V模型会产生大量的冗余轮廓,而且无法分割多个同质区域的目标.为此,提出了基于C-V模型的窄带多区域水平集图像分割方法,采用N-1个水平集函数将图像分割成N(N＞1)个区域,每个水平集函数表达一个区域.该方法一方面通过建立独立多区域水平集模型可以消除多余的轮廓,避免分割区域的重叠...