Dim small target detection based on stochastic resonance

Nong Sang; Ruolin Wang; Haitao Gan; Jian Du; Qiling Tang

doi:10.1117/12.2015633

29 April 2013 Dim small target detection based on stochastic resonance

Nong Sang, Ruolin Wang, Haitao Gan, Jian Du, Qiling Tang

Proceedings Volume 8748, Optical Pattern Recognition XXIV; 87480S (2013) https://doi.org/10.1117/12.2015633
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Dim small target detection, which is characterized by complex background and low Signal-to-Noise Ratio (SNR), is critical for many applications. Traditional detection algorithms assume that noise is not useful for detecting targets and try to remove the noise to improve SNR of images using various filtering techniques. In this paper, we introduce a detection algorithm based on Stochastic Resonance (SR) where stochastic resonance is used to enhance the dim small targets. Our intuition is that SR can achieve the target enhancement in the presence of noise. Adaptive Least Mean Square (ALMS) filtering is first adopted to estimate the background, and the clutter is suppressed by subtracting the estimated background image from the source image. Adaptive SR (ASR) method is then employed to enhance the target and improve the SNR of the image containing the target and noise. ASR tunes and adds the optimal noise intensity to increase the power of the targets and therefore improve the SNR of the image. Several experiments on synthetic and natural images are conducted to evaluate our proposed algorithm. The results demonstrate the effectiveness of our algorithm.

Citation Download Citation

Nong Sang, Ruolin Wang, Haitao Gan, Jian Du, and Qiling Tang "Dim small target detection based on stochastic resonance", Proc. SPIE 8748, Optical Pattern Recognition XXIV, 87480S (29 April 2013); https://doi.org/10.1117/12.2015633

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