Multispectral image compression algorithms

Published

Conference Paper

© 1993 IEEE. This paper presents a data compression algorithm capable of significantly reducing the amounts of information contained in multispectral and hyperspectral images. The loss of information ranges from a perceptually lossless level, achieved at 20-30:1 compression ratios, to a one where exploitation of the images is still possible (over 100:1 ratios). A one-dimensional transform coder removes the spectral redundancy, and a two-dimensional wavelet transform removes the spatial redundancy of multispectral images. The transformed images are subsequently divided into active regions that contain significant wavelet coefficients. Each active block is then hierarchically encoded using multidimensional bitmap trees. Application of reversible histogram equalization methods on the spectral bands can significantly increase the compression/distortion performance. Landsat Thematic Mapper data are used to illustrate the performance of the proposed algorithm.

Full Text

Duke Authors

Cited Authors

  • Markas, T; Reif, J

Published Date

  • January 1, 1993

Published In

Start / End Page

  • 391 - 400

International Standard Serial Number (ISSN)

  • 1068-0314

International Standard Book Number 10 (ISBN-10)

  • 0818633921

Digital Object Identifier (DOI)

  • 10.1109/DCC.1993.253110

Citation Source

  • Scopus