Paper
4 May 2010 Dim point target detection against bright background
Yao Zhang, Qiheng Zhang, Zhiyong Xu, Junping Xu
Author Affiliations +
Abstract
For target detection within a large-field cluttered background from a long distance, several difficulties, involving low contrast between target and background, little occupancy, illumination ununiformity caused by vignetting of lens, and system noise, make it a challenging problem. The existing approaches to dim target detection can be roughly divided into two categories: detection before tracking (DBT) and tracking before detection (TBD). The DBT-based scheme has been widely used in practical applications due to its simplicity, but it often requires working in the situation with a higher signal-to-noise ratio (SNR). In contrast, the TBD-based methods can provide impressive detection results even in the cases of very low SNR; unfortunately, the large memory requirement and high computational load prevents these methods from real-time tasks. In this paper, we propose a new method for dim target detection. We address this problem by combining the advantages of the DBT-based scheme in computational efficiency and of the TBD-based in detection capability. Our method first predicts the local background, and then employs the energy accumulation and median filter to remove background clutter. The dim target is finally located by double window filtering together with an improved high order correlation which speeds up the convergence. The proposed method is implemented on a hardware platform and performs suitably in outside experiments.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yao Zhang, Qiheng Zhang, Zhiyong Xu, and Junping Xu "Dim point target detection against bright background", Proc. SPIE 7724, Real-Time Image and Video Processing 2010, 77240J (4 May 2010); https://doi.org/10.1117/12.853574
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KEYWORDS
Target detection

Signal to noise ratio

Digital filtering

Image segmentation

Image filtering

Target recognition

Detection and tracking algorithms

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