Sparsity divergence index based on locally linear embedding for hyperspectral anomaly detection-Reference-Cited by-同舟云学术

Sparsity divergence index based on locally linear embedding for hyperspectral anomaly detection

Published:2016-06-28 Issue:2 Volume:10 Page:025026
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:en
Short-container-title:J. Appl. Remote Sens

Author:

Zhang Lili¹,Zhao Chunhui²

Affiliation:

1. Harbin Engineering University, College of Information and Communication Engineering, Room 504, Building 21, No. 145 Nantong Street, Nangang District, Harbin City, Heilongjiang Province 150001, ChinabDaqing Normal University, College of Mechanical and Elec

2. Harbin Engineering University, College of Information and Communication Engineering, Room 504, Building 21, No. 145 Nantong Street, Nangang District, Harbin City, Heilongjiang Province 150001, China

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Reference33 articles.

1. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

2. Kernel-based methods for hyperspectral image classification

3. A tutorial overview of anomaly detection in hyperspectral images

4. Hyperspectral imagery: clutter adaptation in anomaly detection

5. Target Detection Under Misspecified Models in Hyperspectral Images

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