Infrared small target detection based on target-background separation via local MCA sparse representation

Hao Fu; Yunli Long; Jungang Yang; Wei An

doi:10.1117/12.2281782

21 July 2017 Infrared small target detection based on target-background separation via local MCA sparse representation

Hao Fu, Yunli Long, Jungang Yang, Wei An

Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 104200X (2017) https://doi.org/10.1117/12.2281782
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China

Abstract

Infrared small target detection is one of the vital techniques in infrared search and track surveillance systems. An efficient method based on target-background separation via local morphological component analysis (MCA) sparse representation is proposed in this paper. This method converts infrared small target detection problem over entire image into target-background separation over image patches according to the different morphological component between target and background. An adaptive dictionary is trained adaptively by K-singular value decomposition (K-SVD) according to infrared image, and then the dictionary is subdivided by a total-variation-like activity measure into two categories: the target component dictionary explaining target signal and background component dictionary embedding background. Finally, the interest target can be easily extracted through threshold segmentation in target component image constructed by target dictionary. The experimental results demonstrate the effectiveness of the proposed method.

Citation Download Citation

Hao Fu, Yunli Long, Jungang Yang, and Wei An "Infrared small target detection based on target-background separation via local MCA sparse representation", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104200X (21 July 2017); https://doi.org/10.1117/12.2281782

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