A novel scheme for the compression and classification of hyperspectral images

Bei Xie, Tamal Bose, Erzsébet Merényi

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

1 Citation (Scopus)

Abstract

Since hyperspectral images are very large, it is desirable to compress them before transmission. After receiving the compressed image, decompression is applied before performing image classification and other operations. In this paper, a new processing scheme is proposed, where image transform and quantization are applied for image compression at the transmitter and classification is performed directly on the compressed data at the receiver. The advantage of this scheme is that fewer computations are needed. Computer simulations are performed on hyperspectral imagery.

Original languageEnglish (US)
Title of host publicationWHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
DOIs
StatePublished - 2009
Externally publishedYes
EventWHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing - Grenoble, France
Duration: Aug 26 2009Aug 28 2009

Other

OtherWHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
CountryFrance
CityGrenoble
Period8/26/098/28/09

Fingerprint

Quantization (signal)
Image classification
Image compression
Transmitters
Computer simulation
Processing

Keywords

  • Hyperspectral imagery
  • Image classification
  • Lossy data compression
  • Neural network

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Xie, B., Bose, T., & Merényi, E. (2009). A novel scheme for the compression and classification of hyperspectral images. In WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing [5289075] https://doi.org/10.1109/WHISPERS.2009.5289075

A novel scheme for the compression and classification of hyperspectral images. / Xie, Bei; Bose, Tamal; Merényi, Erzsébet.

WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing. 2009. 5289075.

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

Xie, B, Bose, T & Merényi, E 2009, A novel scheme for the compression and classification of hyperspectral images. in WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing., 5289075, WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Grenoble, France, 8/26/09. https://doi.org/10.1109/WHISPERS.2009.5289075
Xie B, Bose T, Merényi E. A novel scheme for the compression and classification of hyperspectral images. In WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing. 2009. 5289075 https://doi.org/10.1109/WHISPERS.2009.5289075
Xie, Bei ; Bose, Tamal ; Merényi, Erzsébet. / A novel scheme for the compression and classification of hyperspectral images. WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing. 2009.
@inproceedings{347b3b34989843ef91c06f7cdd9d9487,
title = "A novel scheme for the compression and classification of hyperspectral images",
abstract = "Since hyperspectral images are very large, it is desirable to compress them before transmission. After receiving the compressed image, decompression is applied before performing image classification and other operations. In this paper, a new processing scheme is proposed, where image transform and quantization are applied for image compression at the transmitter and classification is performed directly on the compressed data at the receiver. The advantage of this scheme is that fewer computations are needed. Computer simulations are performed on hyperspectral imagery.",
keywords = "Hyperspectral imagery, Image classification, Lossy data compression, Neural network",
author = "Bei Xie and Tamal Bose and Erzs{\'e}bet Mer{\'e}nyi",
year = "2009",
doi = "10.1109/WHISPERS.2009.5289075",
language = "English (US)",
isbn = "9781424446872",
booktitle = "WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing",

}

TY - GEN

T1 - A novel scheme for the compression and classification of hyperspectral images

AU - Xie, Bei

AU - Bose, Tamal

AU - Merényi, Erzsébet

PY - 2009

Y1 - 2009

N2 - Since hyperspectral images are very large, it is desirable to compress them before transmission. After receiving the compressed image, decompression is applied before performing image classification and other operations. In this paper, a new processing scheme is proposed, where image transform and quantization are applied for image compression at the transmitter and classification is performed directly on the compressed data at the receiver. The advantage of this scheme is that fewer computations are needed. Computer simulations are performed on hyperspectral imagery.

AB - Since hyperspectral images are very large, it is desirable to compress them before transmission. After receiving the compressed image, decompression is applied before performing image classification and other operations. In this paper, a new processing scheme is proposed, where image transform and quantization are applied for image compression at the transmitter and classification is performed directly on the compressed data at the receiver. The advantage of this scheme is that fewer computations are needed. Computer simulations are performed on hyperspectral imagery.

KW - Hyperspectral imagery

KW - Image classification

KW - Lossy data compression

KW - Neural network

UR - http://www.scopus.com/inward/record.url?scp=72049130299&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=72049130299&partnerID=8YFLogxK

U2 - 10.1109/WHISPERS.2009.5289075

DO - 10.1109/WHISPERS.2009.5289075

M3 - Conference contribution

AN - SCOPUS:72049130299

SN - 9781424446872

BT - WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

ER -