Compression of hyperspectral images using significant pixel information of wavelet transforms

Sangwook Lee, Joan Serra Sagrista, Chulhee Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose a compression algorithm for hyperspectral images based on the wavelet transform using adjacent information. A characteristic of the SPIHT algorithm is that it provides information on the locations of significant coefficients of transformed images. On the other hand, there exist high correlation between spectral band images of hyperspectral data. Thus, by using the location information of significant pixels, it is possible to efficiently compress adjacent band images by allocating all available bits to encode the magnitudes of significant pixels. However, some significant pixels would be inevitably missed, resulting in noticeable errors. In this paper, we propose to encode these missed significant pixels to improve coding efficiency. Experiments suggest that taking care of missed significant pixels provides improved performance.

Original languageEnglish
Title of host publication2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
Pages3549-3552
Number of pages4
DOIs
Publication statusPublished - 2006 Dec 1
Event2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS - Denver, CO, United States
Duration: 2006 Jul 312006 Aug 4

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Other

Other2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
CountryUnited States
CityDenver, CO
Period06/7/3106/8/4

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

Cite this

Lee, S., Sagrista, J. S., & Lee, C. (2006). Compression of hyperspectral images using significant pixel information of wavelet transforms. In 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS (pp. 3549-3552). [4242058] (International Geoscience and Remote Sensing Symposium (IGARSS)). https://doi.org/10.1109/IGARSS.2006.910