Robust hyperspectral image coding with channel-optimized trellis-coded quantization

Glen P. Abousleman, Tuyet Trang Lam, Lina Karam

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

This paper presents a wavelet-based hyperspectral image coder that is optimized for transmission over the binary symmetric channel (BSC). The proposed coder uses a robust channel-optimized trellis-coded quantization (COTCQ) stage that is designed to optimize the image coding based on the channel characteristics. This optimization is performed only at the level of the source encoder and does not include any channel coding for error protection. The robust nature of the coder increases the security level of the encoded bit stream, and provides a much higher quality decoded image. In the absence of channel noise, the proposed coder is shown to achieve a compression ratio greater than 70:1, with an average peak SNR of the coded hyperspectral sequence exceeding 40 dB. Additionally, the coder is shown to exhibit graceful degradation with increasing channel errors.

Original languageEnglish (US)
Pages (from-to)820-830
Number of pages11
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume40
Issue number4
DOIs
StatePublished - Apr 1 2002

Keywords

  • Data compression
  • Hyperspectral image compression
  • Multispectral image coding

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

Fingerprint Dive into the research topics of 'Robust hyperspectral image coding with channel-optimized trellis-coded quantization'. Together they form a unique fingerprint.

  • Cite this