This paper proposes a finite adaptive neighborhood suppression algorithm based on singular value decomposition for small target detection in the infrared imaging system. The algorithm firstly does singular value decomposition on the whole gray image, selecting the larger singular values to reconstruct the image and achieving the purpose of noise suppression, thereby obtaining the image matrix contains only weak point of the target and its possible. Then, the pixels are divided into foreground and background in the fixed neighborhood followed by contrast enhancement. Experimental results show that this method can effectively preserve image details and the inhibiting effect is better.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
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.