A new method for reversible compression of multispectral images is presented. 3-D data are decorrelated by means of an inter-band causal prediction obtained through the fuzzy switching of a set of predictors representative of 3-D micro-patterns occurring across bands, whose coefficients are LS-estimated in a preliminary learning phase. The outcome residuals are entropy coded by exploiting context information. Results of compression on both Landsat TM and AVIRIS images show that the proposed approach outperforms other schemes reported by the most recent and advanced literature.

Reversible Compression of Hyper-Spectral Imagery through Inter-Band Fuzzy Prediction and Context Coding

Bruno Aiazzi;Luciano Alparone;Stefano Baronti
1998

Abstract

A new method for reversible compression of multispectral images is presented. 3-D data are decorrelated by means of an inter-band causal prediction obtained through the fuzzy switching of a set of predictors representative of 3-D micro-patterns occurring across bands, whose coefficients are LS-estimated in a preliminary learning phase. The outcome residuals are entropy coded by exploiting context information. Results of compression on both Landsat TM and AVIRIS images show that the proposed approach outperforms other schemes reported by the most recent and advanced literature.
1998
Istituto di Fisica Applicata - IFAC
0-7803-4403-0
Reversible compression
hyper-spectral imagery
inter-band fuzzy prediction
context coding
LS estimation
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/230391
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 9
  • ???jsp.display-item.citation.isi??? ND
social impact