High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows

Yuan Li; Lu Li; Wei Li

doi:10.1109/ICSIDP47821.2019.9173477

High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows

Yuan Li
, Lu Li
, Wei Li

School of Information and Electronics

Beijing University of Chemical Technology

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

Abstract

Hyperspectral image (HSI) object detection have received increasing attention. However, while obtaining rich information through hyperspectral imaging, it brings new challenges to the real-time processing of high-accuracy detection. In this paper, a near real-time parallel algorithm based on sliding dual-windows is proposed, which can be used for object detection in hyperspectral image. First, the Sherman-form is employed to complete the transformation between the sliding dual-windows, so that the process of target or anomaly detection is iteratively calculated. Then, the detection algorithm parallel implement by using GPU to further increase the processing speed. The experimental results demonstrated that the proposed method was more effective than the compared method.

Original language	English
Title of host publication	ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728123455
DOIs	https://doi.org/10.1109/ICSIDP47821.2019.9173477
Publication status	Published - Dec 2019
Event	2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 - Chongqing, China Duration: 11 Dec 2019 → 13 Dec 2019

Publication series

Name	ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019

Conference

Conference	2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019
Country/Territory	China
City	Chongqing
Period	11/12/19 → 13/12/19

Keywords

Hyperspectral imaging
Near Real-time processing
Target and anomaly detection

Access to Document

10.1109/ICSIDP47821.2019.9173477

Cite this

Li, Y., Li, L., & Li, W. (2019). High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows. In ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019 Article 9173477 (ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSIDP47821.2019.9173477

Li, Yuan ; Li, Lu ; Li, Wei. / High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows. ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019).

@inproceedings{27a15e0e8c664cc99ed8d42de1afb5ae,

title = "High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows",

abstract = "Hyperspectral image (HSI) object detection have received increasing attention. However, while obtaining rich information through hyperspectral imaging, it brings new challenges to the real-time processing of high-accuracy detection. In this paper, a near real-time parallel algorithm based on sliding dual-windows is proposed, which can be used for object detection in hyperspectral image. First, the Sherman-form is employed to complete the transformation between the sliding dual-windows, so that the process of target or anomaly detection is iteratively calculated. Then, the detection algorithm parallel implement by using GPU to further increase the processing speed. The experimental results demonstrated that the proposed method was more effective than the compared method.",

keywords = "Hyperspectral imaging, Near Real-time processing, Target and anomaly detection",

author = "Yuan Li and Lu Li and Wei Li",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 ; Conference date: 11-12-2019 Through 13-12-2019",

year = "2019",

month = dec,

doi = "10.1109/ICSIDP47821.2019.9173477",

language = "English",

series = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",

address = "United States",

}

Li, Y, Li, L & Li, W 2019, High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows. in ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019., 9173477, ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019, Chongqing, China, 11/12/19. https://doi.org/10.1109/ICSIDP47821.2019.9173477

High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows. / Li, Yuan; Li, Lu; Li, Wei.
ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 9173477 (ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019).

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

TY - GEN

T1 - High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows

AU - Li, Yuan

AU - Li, Lu

AU - Li, Wei

PY - 2019/12

Y1 - 2019/12

N2 - Hyperspectral image (HSI) object detection have received increasing attention. However, while obtaining rich information through hyperspectral imaging, it brings new challenges to the real-time processing of high-accuracy detection. In this paper, a near real-time parallel algorithm based on sliding dual-windows is proposed, which can be used for object detection in hyperspectral image. First, the Sherman-form is employed to complete the transformation between the sliding dual-windows, so that the process of target or anomaly detection is iteratively calculated. Then, the detection algorithm parallel implement by using GPU to further increase the processing speed. The experimental results demonstrated that the proposed method was more effective than the compared method.

AB - Hyperspectral image (HSI) object detection have received increasing attention. However, while obtaining rich information through hyperspectral imaging, it brings new challenges to the real-time processing of high-accuracy detection. In this paper, a near real-time parallel algorithm based on sliding dual-windows is proposed, which can be used for object detection in hyperspectral image. First, the Sherman-form is employed to complete the transformation between the sliding dual-windows, so that the process of target or anomaly detection is iteratively calculated. Then, the detection algorithm parallel implement by using GPU to further increase the processing speed. The experimental results demonstrated that the proposed method was more effective than the compared method.

KW - Hyperspectral imaging

KW - Near Real-time processing

KW - Target and anomaly detection

UR - https://www.scopus.com/pages/publications/85091951895

U2 - 10.1109/ICSIDP47821.2019.9173477

DO - 10.1109/ICSIDP47821.2019.9173477

M3 - Conference contribution

AN - SCOPUS:85091951895

T3 - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019

BT - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

Y2 - 11 December 2019 through 13 December 2019

ER -

Li Y, Li L, Li W. High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows. In ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 9173477. (ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019). doi: 10.1109/ICSIDP47821.2019.9173477

High-parallel Hyperspectral Image Detection Algorithm by Sherman-Morrison Calculation of Dual-Windows

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