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Author:

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

Indexed by:

EI Scopus

Abstract:

Huge amounts of data of hyperspectral images have become a great challenge to data storage and transmission. In the mean time, as this kind of image is used extensively and any information shouldn't be lost during compression, the lossless compression method seems to be essential. Without an efficient compression scheme, the application of hyperspectral images will be limited. Trellis coded quantization (TCQ) uses the expanded signal set, set partitioning and trellis state transferring ideas from trellis coded modulation (TCM). The mean squared error (MSE) performance of TCQ is excellent with modest computing complexity. At present TCQ is often used for image lossy compression. In this paper, we aim to develop TCQ scheme to compress hyperspectral images losslessly taking advantage of the characteristics of hyperspectral data for compression. A scheme utilizing wavelet transform and trellis coded quantization is presented. Experiment results show that the method presented in this paper has good performance. © 2005 IEEE.

Keyword:

Computational complexity Wavelet transforms Storage allocation (computer) Image coding Image compression

Author Community:

  • [ 1 ] [Wang, Jin]Signal and Information Processing Lab., Beijing University of Technology, Beijing, 100022, China
  • [ 2 ] [Zhang, Xiao-Ling]Signal and Information Processing Lab., Beijing University of Technology, Beijing, 100022, China
  • [ 3 ] [Shen, Lan-Sun]Signal and Information Processing Lab., Beijing University of Technology, Beijing, 100022, China
  • [ 4 ] [Chai, Yan]Signal and Information Processing Lab., Beijing University of Technology, Beijing, 100022, China

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Year: 2005

Volume: I

Page: 1405-1408

Language: English

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 7

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