Compression of hyperspectral images with enhanced discriminant features

Chulhee Lee; Euisun Choi

doi:10.1109/WARSD.2003.1295176

Compression of hyperspectral images with enhanced discriminant features

Chulhee Lee, Euisun Choi

Department of Electrical and Electronic Engineering

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

7 Citations (Scopus)

Abstract

We propose compression algorithms for hyperspectral images with enhanced discriminant features. As the dimension of remotely sensed images increases, the need for efficient compression algorithms for hyperspectral images also increases. However, when hyperspectral images are compressed with conventional image compression algorithms, which have been developed to minimize mean squared errors, discriminant features of the original data may be lost during the compression process. In this paper, we propose to apply preprocessing prior to compression in order to preserve such discriminant information. In particular, we enhance discriminant features before a compression algorithm is applied. Experiments show that the proposed method provides improved classification accuracies than the existing compression algorithms.

Original language	English
Title of host publication	2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	76-79
Number of pages	4
ISBN (Electronic)	0780383508, 9780780383500
DOIs	https://doi.org/10.1109/WARSD.2003.1295176
Publication status	Published - 2004
Event	2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data - Greenbelt, United States Duration: 2003 Oct 27 → 2003 Oct 28

Publication series

Name	2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data

Other

Other	2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data
Country/Territory	United States
City	Greenbelt
Period	03/10/27 → 03/10/28

Bibliographical note

Publisher Copyright:
© 2004 IEEE.

All Science Journal Classification (ASJC) codes

Computer Networks and Communications

Access to Document

10.1109/WARSD.2003.1295176

Cite this

Lee, C., & Choi, E. (2004). Compression of hyperspectral images with enhanced discriminant features. In 2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data (pp. 76-79). Article 1295176 (2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WARSD.2003.1295176

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abstract = "We propose compression algorithms for hyperspectral images with enhanced discriminant features. As the dimension of remotely sensed images increases, the need for efficient compression algorithms for hyperspectral images also increases. However, when hyperspectral images are compressed with conventional image compression algorithms, which have been developed to minimize mean squared errors, discriminant features of the original data may be lost during the compression process. In this paper, we propose to apply preprocessing prior to compression in order to preserve such discriminant information. In particular, we enhance discriminant features before a compression algorithm is applied. Experiments show that the proposed method provides improved classification accuracies than the existing compression algorithms.",

author = "Chulhee Lee and Euisun Choi",

note = "Publisher Copyright: {\textcopyright} 2004 IEEE.; 2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data ; Conference date: 27-10-2003 Through 28-10-2003",

year = "2004",

doi = "10.1109/WARSD.2003.1295176",

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series = "2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data",

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Lee, C & Choi, E 2004, Compression of hyperspectral images with enhanced discriminant features. in 2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data., 1295176, 2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, Institute of Electrical and Electronics Engineers Inc., pp. 76-79, 2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, Greenbelt, United States, 03/10/27. https://doi.org/10.1109/WARSD.2003.1295176

Compression of hyperspectral images with enhanced discriminant features. / Lee, Chulhee; Choi, Euisun.
2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data. Institute of Electrical and Electronics Engineers Inc., 2004. p. 76-79 1295176 (2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data).

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

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AB - We propose compression algorithms for hyperspectral images with enhanced discriminant features. As the dimension of remotely sensed images increases, the need for efficient compression algorithms for hyperspectral images also increases. However, when hyperspectral images are compressed with conventional image compression algorithms, which have been developed to minimize mean squared errors, discriminant features of the original data may be lost during the compression process. In this paper, we propose to apply preprocessing prior to compression in order to preserve such discriminant information. In particular, we enhance discriminant features before a compression algorithm is applied. Experiments show that the proposed method provides improved classification accuracies than the existing compression algorithms.

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Lee C, Choi E. Compression of hyperspectral images with enhanced discriminant features. In 2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data. Institute of Electrical and Electronics Engineers Inc. 2004. p. 76-79. 1295176. (2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data). doi: 10.1109/WARSD.2003.1295176

Compression of hyperspectral images with enhanced discriminant features

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