1 April 2002 Small target pre-detection with an attention mechanism
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We introduce the concept of predetection based on an attention mechanism to improve the efficiency of small-target detection by limiting the image region of detection. According to the characteristics of small-target detection, local contrast is taken as the only feature in predetection and a nonlinear sampling model is adopted to make the predetection adaptive to detect small targets with different area sizes. To simplify the predetection itself and decrease the false alarm probability, neighboring nodes in the sampling grid are used to generate a saliency map, and a short-term memory is adopted to accelerate the "pop-out" of targets. We discuss the fact that the proposed approach is simple enough in computational complexity. In addition, even in a cluttered background, attention can be led to targets in a satisfying few iterations, which ensures that the detection efficiency will not be decreased due to false alarms. Experimental results are presented to demonstrate the applicability of the approach.
©(2002) Society of Photo-Optical Instrumentation Engineers (SPIE)
Yuehuan Wang, Tianxu Zhang, and Guoyou Wang "Small target pre-detection with an attention mechanism," Optical Engineering 41(4), (1 April 2002). https://doi.org/10.1117/1.1459054
Published: 1 April 2002
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Cited by 9 scholarly publications.
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KEYWORDS
Signal to noise ratio

Target detection

Optical engineering

Gaussian filters

Digital signal processing

Visual process modeling

Image enhancement

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