J4 ›› 2013, Vol. 40 ›› Issue (4): 108-113.doi: 10.3969/j.issn.1001-2400.2013.04.018

• 研究论文 • 上一篇    下一篇

利用免疫克隆进行小波域遥感图像变化检测

王凌霞1;焦李成1;颜学颖1;辛芳芳2   

  1. (1. 西安电子科技大学 智能感知与图像理解教育部重点实验室,陕西 西安  710071;
    2. 西安微电子技术研究所,陕西 西安  710054)
  • 收稿日期:2013-01-23 出版日期:2013-08-20 发布日期:2013-10-10
  • 通讯作者: 王凌霞
  • 作者简介:王凌霞(1983-),女,西安电子科技大学博士研究生,E-mail: wanglingxia@163.com.
  • 基金资助:

    国家自然科学基金资助项目(61001202,61003199);高等学校学科创新引智计划(111计划)资助项目(B07048);国家教育部博士点基金资助项目(200807010003,20090203120016,20100203120008);教育部“长江学者和创新团队发展计划”资助项目(IRT1170)

Change detection in multi-temporal remote sensing images based on the wavelet-domain immune clonal optimazition

WANG Lingxia1;JIAO Licheng1;YAN Xueying1;XIN Fangfang2   

  1. (1. Ministry of Education Key Lab. of Intelligent Perception and Image Understanding, Xidian Univ., Xi'an  710071, China;
    2. Xi'an Institute of Microelectronics Technology, Xi'an  710054, China)
  • Received:2013-01-23 Online:2013-08-20 Published:2013-10-10
  • Contact: WANG Lingxia

摘要:

为了降低遥感图像变化检测中噪声对检测精度的影响,提出一种基于免疫克隆结合小波变换的新算法.首先利用小波多尺度和低通平滑的特性,构造多层差异影像;再通过免疫克隆算法修正小波变换插零和卷积操作带来的图像空域偏差,对运用瑞利高斯模型分割得到的初始结果进行二次线性插值的匹配;最后经图像融合得到变化检测结果.仿真实验表明,这种算法不仅降低了图像噪声的影响,而且有效地抑制了由小波变换带来的图像偏移误差,显著地提高了变化检测精度.

关键词: 变化检测, 免疫克隆算法, 小波变换

Abstract:

In order to reduce the impact of noises on detection accuracy in change detection for remote sensing images, a novel change detection method is proposed based on the immune clone algorithm and wavelet transform. Firstly, the multi-scale and low-pass smoothing characteristics of wavelet transform are utilized to construct multi-layered difference images. Secondly the time domain deviations caused by operation of zero insertion and image convolution in wavelet transform are corrected by the immune clonal algorithm that the initial segmentation results obtained using the Rayleigh-Gauss model are matched by the secondary linear interpolation operation. Finally, the change detection is accomplished by image fusion. Simulation results show that the algorithm can not only reduce the image noises, but also suppress the image deviations caused by wavelet transform effectively. The accuracy of change detection is improved significantly.

Key words: change detection, immune clonal algorithm, wavelet transform