A novel scheme for the compression and classification of hyperspectral images

Bei Xie; Tamal Bose; Erzsébet Merényi

doi:10.1109/WHISPERS.2009.5289075

A novel scheme for the compression and classification of hyperspectral images

Bei Xie, Tamal Bose, Erzsébet Merényi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

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 language	English (US)
Title of host publication	WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publication	Evolution in Remote Sensing
DOIs	https://doi.org/10.1109/WHISPERS.2009.5289075
State	Published - Dec 21 2009
Externally published	Yes
Event	WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing - Grenoble, France Duration: Aug 26 2009 → Aug 28 2009

Publication series

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

Other

Other	WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
Country	France
City	Grenoble
Period	8/26/09 → 8/28/09

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

Access to Document

10.1109/WHISPERS.2009.5289075

Fingerprint Dive into the research topics of 'A novel scheme for the compression and classification of hyperspectral images'. Together they form a unique fingerprint.

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] (WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing). 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 (WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing).

Research output: Chapter in Book/Report/Conference proceeding › Conference 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, 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. (WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing). https://doi.org/10.1109/WHISPERS.2009.5289075

@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",

month = dec,

day = "21",

doi = "10.1109/WHISPERS.2009.5289075",

language = "English (US)",

isbn = "9781424446872",

series = "WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing",

booktitle = "WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing",

note = "WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing ; Conference date: 26-08-2009 Through 28-08-2009",

}

TY - GEN

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

AU - Xie, Bei

AU - Bose, Tamal

AU - Merényi, Erzsébet

PY - 2009/12/21

Y1 - 2009/12/21

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

T3 - WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

BT - WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing

T2 - WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

Y2 - 26 August 2009 through 28 August 2009

ER -