跳到主要导航 跳到搜索 跳到主要内容

Adaptive non-dominated sorting genetic algorithms for wavelength selection of molecular hyperspectral images

  • Qingli Li*
  • , Jingao Liu
  • , Yiting Wang
  • , Chunni Dai
  • *此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Hyperspectral data cube usually includes hundreds of high-correlated single band images. It is necessary to reduce the dimensionality of hyperspectral images to facilitate the studies and analysis. This paper presents an adaptive non-dominated sorting genetic algorithm to process the wavelength combination of molecular hyperspectral images. In this algorithm, dynamic reproduction probabilities are employed to regulate the selection pressure. To evaluate the performance of this new algorithm on the combination optimization, the simulation results are compared with those of a non-dominated sorting genetic algorithm without adaptation and of a single-objective genetic algorithm having the same adaptive mechanism. The comparison revealed its better performance in the wavelength selection of molecular hyperspectral data of rat retinal sections.

源语言英语
主期刊名Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010
82-85
页数4
DOI
出版状态已出版 - 2010
活动3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010 - Yantai, 中国
期限: 16 10月 201018 10月 2010

出版系列

姓名Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010
1

会议

会议3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010
国家/地区中国
Yantai
时期16/10/1018/10/10

引用此