Hyperspectral Image Compression Using 3-D discrete cosine transform and entropy-constrained trellis coded quantization

Glen P. Abousleman, Michael W. Marcellin, Bobby R. Hunt

Research output: Contribution to journalConference article

4 Scopus citations

Abstract

A system is presented for compression of hyperspectral imagery which utifizes treffis coded quantization (TCQ). Specifically, TCQ is ued to encode transform coefficients resulting from the application of an 8 x 8 x 8 discrete cosine transform. Side information and rate allocation strategies are discussed. Entropy-constrained codebooks are designed using a modified version of the generalized Lloyd algorithm. This entropy constrained system achieves a compression ratio of greater than 70:1 with an average PSNR of the coded hyperspectral sequence exceeding 40.5 dB.

Original languageEnglish (US)
Pages (from-to)136-147
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume2231
DOIs
StatePublished - Jul 8 1994
EventAlgorithms for Multispectral and Hyperspectral Imagery 1994 - Orlando, United States
Duration: Apr 4 1994Apr 8 1994

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Hyperspectral Image Compression Using 3-D discrete cosine transform and entropy-constrained trellis coded quantization'. Together they form a unique fingerprint.

  • Cite this