Basic Theory and Main Processing Techniques of Hyperspectral Remote Sensing

  • Liguo WangEmail author
  • Chunhui Zhao


In order to enable the readers to have a better understanding of the main body contents of this book, this chapter firstly introduces the basic theory of the hyperspectral remote-sensing technique, involving the electromagnetic wave, solar radiation, imaging spectrometer and spectral imaging modes etc.


Hyperspectral Image Hyperspectral Data Lossless Compression Hopfield Neural Network Super Resolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Li ES, Zhang BM, Song LH, Yu WJ, Tang DJ (2011) A review on spectral unmixing algorithms based on linear mixing model. Sci Surv Mapp 36(5):42–44Google Scholar
  2. Liu CH (2005) Research on dimensional reduction and classification of hyperspectral remote sensing image. Harbin Engineering University, NangangGoogle Scholar
  3. Ren W, Ge Y (2011) Progress on sub-pixel mapping methods for remotely sensed images. Remote Sens Technol Appl 26(1):33–44Google Scholar
  4. Sun JB (2003) Remote sensing principle and application. Wuhan University Press, Wuhan, pp 210–211Google Scholar
  5. Tong QX, Zhang B, Zheng LF (2006) Hyperspectral remote sensing: principle, technology and application. Higher Education Press, BeijingGoogle Scholar
  6. Wan JW, Nian YJ, Su LH, Xin Q (2010) Research progress on hyperspectral imagery compression technique. Sig Process 26(9):1397–1407Google Scholar

Copyright information

© National Defense Industry Press, Beijing and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Harbin Engineering UniversityHarbinChina

Personalised recommendations