Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification

Zexuan Zhu; Linlin Shen; Yiwen Sun; Shan He; Zhen Ji

doi:10.1007/978-3-642-30976-2_58

Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification

Zexuan Zhu, Linlin Shen, Yiwen Sun, Shan He, Zhen Ji^*

^*Corresponding author for this work

Computer Science

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

4 Citations (Scopus)

Abstract

This paper proposes a three-dimensional Gabor feature extraction for pixel-based hyperspectral imagery classification using a memetic algorithm. The proposed algorithm named MGFE combines 3-D Gabor wavelet feature generation and feature selection together to capture the signal variances of hyperspectral imagery, thereby extracting the discriminative 3-D Gabor features for accurate classification. MGFE is characterized with a novel fitness evaluation function based on independent feature relevance and a pruning local search for eliminating redundant features. The experimental results on two real-world hyperspectral imagery datasets show that MGFE succeeds in obtaining significantly improved classification accuracy with parsimonious feature selection.

Original language	English
Title of host publication	Advances in Swarm Intelligence - Third International Conference, ICSI 2012, Proceedings
Pages	479-488
Number of pages	10
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-30976-2_58
Publication status	Published - 2012
Event	3rd International Conference on Swarm Intelligence, ICSI 2012 - Shenzhen, China Duration: 17 Jun 2012 → 20 Jun 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	7331 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Swarm Intelligence, ICSI 2012
Country/Territory	China
City	Shenzhen
Period	17/06/12 → 20/06/12

Bibliographical note

Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.

Keywords

Gabor Feature Extraction
Hyperspectral Imagery Classification
Memetic Algorithm

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-30976-2_58

Cite this

Zhu, Z., Shen, L., Sun, Y., He, S., & Ji, Z. (2012). Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification. In Advances in Swarm Intelligence - Third International Conference, ICSI 2012, Proceedings (PART 1 ed., pp. 479-488). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7331 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-30976-2_58

Zhu, Zexuan ; Shen, Linlin ; Sun, Yiwen et al. / Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification. Advances in Swarm Intelligence - Third International Conference, ICSI 2012, Proceedings. PART 1. ed. 2012. pp. 479-488 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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abstract = "This paper proposes a three-dimensional Gabor feature extraction for pixel-based hyperspectral imagery classification using a memetic algorithm. The proposed algorithm named MGFE combines 3-D Gabor wavelet feature generation and feature selection together to capture the signal variances of hyperspectral imagery, thereby extracting the discriminative 3-D Gabor features for accurate classification. MGFE is characterized with a novel fitness evaluation function based on independent feature relevance and a pruning local search for eliminating redundant features. The experimental results on two real-world hyperspectral imagery datasets show that MGFE succeeds in obtaining significantly improved classification accuracy with parsimonious feature selection.",

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Zhu, Z, Shen, L, Sun, Y, He, S & Ji, Z 2012, Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification. in Advances in Swarm Intelligence - Third International Conference, ICSI 2012, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7331 LNCS, pp. 479-488, 3rd International Conference on Swarm Intelligence, ICSI 2012, Shenzhen, China, 17/06/12. https://doi.org/10.1007/978-3-642-30976-2_58

Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification. / Zhu, Zexuan; Shen, Linlin; Sun, Yiwen et al.
Advances in Swarm Intelligence - Third International Conference, ICSI 2012, Proceedings. PART 1. ed. 2012. p. 479-488 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7331 LNCS, No. PART 1).

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

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AB - This paper proposes a three-dimensional Gabor feature extraction for pixel-based hyperspectral imagery classification using a memetic algorithm. The proposed algorithm named MGFE combines 3-D Gabor wavelet feature generation and feature selection together to capture the signal variances of hyperspectral imagery, thereby extracting the discriminative 3-D Gabor features for accurate classification. MGFE is characterized with a novel fitness evaluation function based on independent feature relevance and a pruning local search for eliminating redundant features. The experimental results on two real-world hyperspectral imagery datasets show that MGFE succeeds in obtaining significantly improved classification accuracy with parsimonious feature selection.

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Zhu Z, Shen L, Sun Y, He S, Ji Z. Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification. In Advances in Swarm Intelligence - Third International Conference, ICSI 2012, Proceedings. PART 1 ed. 2012. p. 479-488. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-30976-2_58

Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this