期刊文献+

基于逐波段处理的高光谱图像实时目标检测 被引量:3

Progressive Band Processing Algorithm for Hyperspectral Image Real-time Target Detection
下载PDF
导出
摘要 高光谱遥感图像实时目标检测对于实际应用具有十分重要的意义。针对目标和背景光谱均已知的高光谱遥感图像实时目标检测的问题,在正交子空间投影算法的基础上,利用矩阵分析理论,推导出逐波段处理的实时正交子空间投影算法,加强了原算法的实时处理能力。通过真实图像的实验结果表明,逐波段处理算法具有在实时性基础上提前结束检测过程从而减少目标检测过程所需时间的能力,并且具有数据存储空间和算法运算时间上的优越性。 In this paper,a progressive orthogonal subspace projection(POSP) algorithm is proposed by introducing matrix analysis theory under the condition of prior knowledge of target and background information.This method is based on the orthogonal subspace projection(OSP) algorithm and enhance the original method to process image in real-time.Experimental results of real data image demonstrate that the proposed POSP algorithm has the potential to finish the detection process earlier,and the advantage of time and space occupation.
作者 周昕 厉小润
出处 《工业控制计算机》 2015年第6期42-44,共3页 Industrial Control Computer
基金 浙江省自然科学基金重点资助项目(LZ14F030004) 浙江省自然科学基金资助项目(LY13F020044) 国家自然科学基金资助项目(61171152)
关键词 正交子空间投影 逐波段处理 实时目标检测 orthogonal subspace projection progressive band process real-time target detection
  • 相关文献

参考文献10

  • 1贺霖,潘泉,邸韡,李远清.高光谱图像目标检测研究进展[J].电子学报,2009,37(9):2016-2024. 被引量:37
  • 2刘振霞,张晓燕,朱子健高光谱图像目标检测技术研究[C]//二○一○国防空天信息技术前沿论坛论文集专题三:天基预警探测技术及应用,2010.
  • 3Yun Youngnam, Sang Jinhong, We Duckcho et.al., Method for realtime target detection based on reduced complexity hyperspectral processing [P], United States Patent LIS8081825, 2011.
  • 4Wang Yulei,Schultz Robert,Chen Shihyu,Liu Chunhong, ChangChein-I,Progressive constrained energy minimization for sub- pixel detection [C]//Proc.SPIE 8743,Algorithm and Technolo- gies for MultispectraI,Hyperspectral and Ultraspectral Imagery XIX, 874321, 2013.
  • 5Bernabe S, Lopez S, Plaza A, et ai. GPU Implementation of an Automatic Target Detection and Classification Algorithm for Hyperspectral Image Analysis[J]. Geoscience and Remote Sensing Letters, IEEE, 2013, 10(2): 221-225.
  • 6耿修瑞,赵永超.高光谱遥感图像小目标探测的基本原理[J].中国科学(D辑),2007,37(8):1081-1087. 被引量:20
  • 7Harsanyi J C, Chein-I C. Hyperspectral image classification and dimensionality reduction: an orthogonal subspace pro- jection approach[J]. Geoscience and Remote Sensing, IEEE Transactions on, 1994, 32(4): 779-785.
  • 8Nascimento J M P,Bioucas Dias J M.Vertex component anal- ysis:a fast algorithm to unmix hyperspectral data [J].Geo- science and Remote Sensing,lEEE Transactions on, 2005, 43 (4): 898-910.
  • 9Chein-I C, Su W, Keng-Hao L, et al. Progressive Band Dimensionality Expansion and Reduction Via Band Prioritiza- tion for Hyperspectral Imagery [J]. Selected Topics in Ap- plied Earth Observations and Remote Sensing, IEEE Journal of, 2011, 4(3): 591-614.
  • 10Chein-I C, Hyperspectral Imaging: Techniques for Spectral Detection and Classification[M]. New York:Plenum, 2003.

二级参考文献66

共引文献55

同被引文献16

引证文献3

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部