Preprocessing Techniques for Hyperspectral-Images

  • YANG Yanjie;ZHAO Yingjun;QIN Kai;LU Donghua
  • National Key Laboratory of Remote Sensing Information and Image Analysis Technique, Beijing Research Institute of Uranium Geology, CNNC, Beijing 100029, China

Received date: 2012-10-08

  Revised date: 2013-02-15

  Online published: 2013-03-28


This paper discusses the processing of the CASI/SASI hyperspectral-image data obtained by Beijing Research Institute of Uranium Geology. The process flow, the technical details and the technical points of the hyperspectral processing are summarized. The problems of the hyperspectral data processing, such as the large hyperspectral data amount, the long processing time and the image stitching difficulties are discussed and the related countermeasures are proposed. A better application model and the technical support are provided for high spatial resolution hyperspectral data. The airborne hyperspectral images would be distorted due to the effect of the terrain, so the high resolution DEM data should be treated by orthorectification. Under different conditions when the ground images are obtained from the equipment on the plane, the same object on two images would have different colors, so the color difference should be eliminated. A great number of tests show that the CROSS model of the ENVI software can eliminate the color difference. As the space and spectral resolutions of the hyperspectral images are improved, the data volume increases. So the problem of the large volume data would add more difficulties and slow the speed of the hyperspectral image disposition. The spare time of the airborne hyperspectral images acquisition procedure should be used to do some work of the hyperspectral image pre-process. The characteristic bands are used to do the re-sampling of the hyperspectral images, which can improve the efficiency and increase the extraction speed of the hyperspectral images.

Cite this article

YANG Yanjie;ZHAO Yingjun;QIN Kai;LU Donghua . Preprocessing Techniques for Hyperspectral-Images[J]. Science & Technology Review, 2013 , 31(9) : 65 -67 . DOI: 10.3981/j.issn.1000-7857.2013.09.011