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作者:

Chai, Yan (Chai, Yan.) | Zhang, Xiao-Ling (Zhang, Xiao-Ling.) | Shen, Lan-Sun (Shen, Lan-Sun.)

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EI Scopus

摘要:

Using the significant spectral correlation within the hyperspectral images, we present a lossless compression algorithm in this paper. By means of band ordering according to spectral correlation coefficient and 2D/3D hybrid predicton, which are based on local texture and neural networks, hyperspectral data are decorrelated. The prediction residuals are then entropy coded by context-based Golomb coding. Experimental results show that this method can remove the spatial and spectral redundancy efficiently and outperforms JPEG-LS and 3D-APA on average bit rate obviously. © 2005 IEEE.

关键词:

Algorithms Correlation methods Image coding Image compression Image quality Neural networks

作者机构:

  • [ 1 ] [Chai, Yan]Signal and Information Processing Lab., Beijing University of Technology, Beijing, China
  • [ 2 ] [Zhang, Xiao-Ling]Signal and Information Processing Lab., Beijing University of Technology, Beijing, China
  • [ 3 ] [Shen, Lan-Sun]Signal and Information Processing Lab., Beijing University of Technology, Beijing, China

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年份: 2005

卷: I

页码: 1409-1412

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 1

ESI高被引论文在榜: 0 展开所有

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