Comparison of hyperspectral unmixing methods for ship detection on airborne hyperspectral images

Tae-Sung Kim; Jae-Jin Park; Kyung-Ae Park; Sangwoo Oh

doi:10.1117/12.2570630

20 September 2020 Comparison of hyperspectral unmixing methods for ship detection on airborne hyperspectral images

Tae-Sung Kim, Jae-Jin Park, Kyung-Ae Park, Sangwoo Oh

Proceedings Volume 11529, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2020; 115290D (2020) https://doi.org/10.1117/12.2570630
Event: SPIE Remote Sensing, 2020, Online Only

Conference Poster

Abstract

As marine traffic has increased, the importance of ship detection using remote sensing images has been emphasized. Especially, with a better performance for discrimination of target, the usage of hyperspectral data for marine surveillance has been increasing recently. In this study, we detected the vessels on airborne hyperspectral images and quantitatively analyzed the detection results. To obtain the airborne hyperspectral images and auxiliary data for the quantitative validation, the in-field airborne imaging experiment was carried out. In addition, four different end-member extraction techniques including N-FINDR, PPI, ICA, and VCA were applied for comparison of detection performance with hyperspectral unmixing methods. Detection results present significant differences by endmember extraction techniques. The N-FINDR and VCA techniques presented a total of 14 vessels, while the ICA technique detected seven vessels, and the PPI technique detected two vessels. The pixel-based probability of detection and false alarm ratiofor all 14 ships were 98.83% and 4.30%, respectively. This study also addressed the important role of abundance fraction analysis for marine surveillance purpose.

Citation Download Citation

Tae-Sung Kim, Jae-Jin Park, Kyung-Ae Park, and Sangwoo Oh "Comparison of hyperspectral unmixing methods for ship detection on airborne hyperspectral images", Proc. SPIE 11529, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2020, 115290D (20 September 2020); https://doi.org/10.1117/12.2570630

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available