计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 184-186.

• 模式识别与图像处理 • 上一篇    下一篇

面向对象的ICA变化检测新方法

李小春,贾春阳,李卫华   

  1. 空军工程大学信息与导航学院 西安710077;空军工程大学信息与导航学院 西安710077;空军工程大学信息与导航学院 西安710077
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受陕西省自然科学基金项目(2012JQ8016)资助

Novel Change Detection Method Using Independent Component Analysis and Oriented-object Method

LI Xiao-chun,JIA Chun-yang and LI Wei-hua   

  • Online:2018-11-14 Published:2018-11-14

摘要: 通过分析高分辨率影像变化检测方法存在的问题,提出了结合面向对象和非抽样小波变换(undecimated discrete wavelet transform,UDWT)的独立成分分析(Independent Component Analysis,ICA)变化检测新算法。利用面向对象处理方法提取的影像对象特征图作为构建ICA子空间估计输入向量的数据,改善了对噪声抑制的效果,同时,提出了自适应权值的影像对象提取算法,进一步优化了面向对象的处理方法;采用非抽样小波变换进行分块有效克服了现有分块方法带来的ICA子空间估计输入向量尺寸缩减、子空间估计不准确的突出问题。 定性定量仿真结果表明 :与典型的ICA算法和UDWT算法相比,新算法在高分辨影像变化检测的准确性和鲁棒性方面都得到了很大的改善。

关键词: 影像对象,变化检测,非抽样小波变换,独立成分分析 中图法分类号TP391.41文献标识码A

Abstract: Through analyzing problems brought on change detection methods of remote sensing images with high resolution,a novel change detection algorithm using Independent Component Analysis combined with oriented-object and undecimated discrete wavelet transform (UDWT) was proposed.First,feature images of image’s objects extracted using oriented-object method serve as data of input vector to estimate sub-space for Independent Component Analysis,which can improve effect of noise suppression,simultaneously,a new algorithm using self-adapted weight was proposed in order to extract image’s object,which optimizes processing method on oriented-object deeply.New partitioning scheme using undecimated discrete wavelet transform overcomes effectively prominent problem as follows:the size of input vector becomes shrinking which leads to unprecisely estimation of sub-space for independent component analysis using present partitioning scheme. Simulation results show that compared with typical algorithm,such as Independent Component Analysis and undecimated discrete wavelet transform, new algorithm improves robust and veracity of change detection for high-resolution images greatly by using qualitative and quantitative results.

Key words: Image’s objects,Change detection,UDWT,ICA

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