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

3 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 - 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/Territory	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

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 Article 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

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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.",

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author = "Bei Xie and Tamal Bose and Erzs{\'e}bet Mer{\'e}nyi",

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A novel scheme for the compression and classification of hyperspectral images

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

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