Parameter optimization for hyperspectral image compression algorithm of maximum error controllable

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In order to improve the efficiency of algorithm, parameter optimization for hyperspectral image compression algorithm of maximum error controllable has been studied in this paper. Firstly, a mathematic optimal model for the hyperspectral image compression ratio was established. Secondly, we analyzed the model and simplified it by Gaussian function. Finally, some real hyperspectral images' compression ratios were estimated using the model. Experiments show the relative error between the estimations and the simulation results is less than 5%, and 31.25% of the both results are exactly the same. In addition, the optimal model saves 70% of running time. These illustrate the high effectiveness and practicability of the optimal model.

Original languageEnglish
Title of host publicationICIST 2014 - Proceedings of 2014 4th IEEE International Conference on Information Science and Technology
EditorsGuoqing Xu, Yu Qiao, Xinyu Wu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages312-315
Number of pages4
ISBN (Electronic)9781479948086
DOIs
Publication statusPublished - 10 Oct 2014
Event2014 4th IEEE International Conference on Information Science and Technology, ICIST 2014 - Shenzhen, China
Duration: 26 Apr 201428 Apr 2014

Publication series

NameICIST 2014 - Proceedings of 2014 4th IEEE International Conference on Information Science and Technology

Conference

Conference2014 4th IEEE International Conference on Information Science and Technology, ICIST 2014
Country/TerritoryChina
CityShenzhen
Period26/04/1428/04/14

Keywords

  • Compression
  • Gaussian function
  • Hyperspectral Image
  • Parameter Optimization

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