Small target detection based on accumulated center-surround difference measure

Abstract Small target detection is a critical problem in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some difficulties remained due to the clutter environment such as the cloud edge and the horizontal line. In the homogeneous area such as sky, cloud-inner area and sea surface area, target can easily be detected, but in heterogeneous area which contains cloud edge, sky-sea line the target may be falsely detected. This paper proposes a novel method called accumulated center-surround difference measure to detect infrared small target in heavy clutter. Each pixel’s accumulated center-surround difference measure is computed by using sliding window manner. The measure can effectively distinguish target region and heterogeneous region. Experimental results show our method achieves better performance.

[1]  Tae-Wuk Bae,et al.  Small target detection using bilateral filter and temporal cross product in infrared images , 2011 .

[2]  Jinwen Tian,et al.  Infrared small target detection using directional highpass filters based on LS-SVM , 2009 .

[3]  Jianguo Liu,et al.  Infrared small target detection based on the self-information map , 2011 .

[4]  Fei Zhao,et al.  Complex background suppression based on fusion of morphological Open filter and nucleus similar pixels bilateral filter , 2012 .

[5]  Jie Yang,et al.  Infrared small target detection using sparse representation , 2011 .

[6]  Xinsheng Huang,et al.  Infrared dim and small target detecting and tracking method inspired by Human Visual System , 2014 .

[7]  Zhiguo Cao,et al.  Fast new small-target detection algorithm based on a modified partial differential equation in infrared clutter , 2007 .

[8]  Meng Hwa Er,et al.  Max-mean and max-median filters for detection of small targets , 1999, Optics & Photonics.

[9]  Yao Zhao,et al.  Bilateral two-dimensional least mean square filter for infrared small target detection , 2014 .

[10]  David W. Thomas,et al.  The two-dimensional adaptive LMS (TDLMS) algorithm , 1988 .

[11]  Xiangzhi Bai,et al.  Analysis of new top-hat transformation and the application for infrared dim small target detection , 2010, Pattern Recognit..

[12]  Jie Yang,et al.  Effective small DIM target detection by local connectedness constraint , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[13]  Yang Liu,et al.  Infrared point target detection with improved template matching , 2012 .

[14]  Lei Yang,et al.  Adaptive detection for infrared small target under sea-sky complex background , 2004 .