1 March 1996 Efficient method for multiscale small target detection from a natural scene
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According to the principle of human discrimination of small targets from a natural scene that there is a signature of discontinuity between the object and its neighboring regions, we develop an efficient method for multiscale small target detection using template matching based on a dissimilarity measure, which is called an average gray absolute difference maximum map (AGADMM), and infer the criterion of recognizing multiscale small objects from the properties of the AGADMM of the natural scene, which is a spatially independent and stable Gaussian random field. We explain how the AGADMM increases the ratio of the signal of object-to-background perturbations, improves the detectable probability, and keeps the false alarm probability very low. We analyze the complexity of computing an AGADMM and justify the validity and efficiency. Experiments with images of a natural scene such as a sky and sea surface have shown the great potential of the proposed method for distinguishing multiscale small objects from a natural scene.
Guoyou Wang, Tianxu Zhang, Luogang Wei, and Nong Sang "Efficient method for multiscale small target detection from a natural scene," Optical Engineering 35(3), (1 March 1996). https://doi.org/10.1117/1.600644
Published: 1 March 1996
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Cited by 53 scholarly publications and 12 patents.
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KEYWORDS
Target detection

Signal to noise ratio

Optical engineering

3D acquisition

3D image processing

Detection and tracking algorithms

Fractal analysis

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