Spectral DPCM for Lossless Compression of 3D Hyperspectral Sounding Data

نویسندگان

  • JARNO MIELIKAINEN
  • OLGA KUBASOVA
  • PEKKA TOIVANEN
چکیده

A spectral linear prediction compression scheme for lossless compression of hyperspectral images is proposed in this paper. Since hyperspectral images have a great deal of correlation from band to band, spectral linear prediction algorithm, which utilizes information from several bands, is very efficient for compression purposes. The proposed algorithm is compared to JPEG-LS and CALIC encoding schemes. All algorithms have been tested on 10 real 3D sounding images and their results in term of compression ratios are shown. Amount of compression obtained by the new algorithm is significantly higher compared to the previously proposed lossless compression methods for hyperspectral images. Key-Words: Hyperspectral images, Sounder images, Lossless compression, Image compression

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تاریخ انتشار 2004