Small target detection combining regional stability and saliency in a color image
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In this paper, we will address the issue of detecting small target in a color image from the perspectives of both stability and saliency. First, we consider small target detection as a stable region extraction problem. Several stability criteria are applied to generate a stability map, which involves a set of locally stable regions derived from sequential boolean maps. Second, considering the local contrast of a small target and its surroundings, we obtain a saliency map by comparing the color vector of each pixel with its Gaussian blurred version. Finally, both the stability and saliency maps are integrated in a pixel-wise multiplication manner for removing false alarms. In addition, we introduce a set of integration models by combining several existing stability and saliency methods, and use them to indicate the validity of the proposed framework. Experimental results show that our model adapts to target size variations and performs favorably in terms of precision, recall and F-measure on three challenging datasets.
KeywordsSmall target detection Stable region Visual saliency Color image
The authors thank all of the anonymous reviewers for their insights and suggestions, which were very helpful in improving this manuscript. They thank Haiyang Zhang for useful discussions. They also thank Mei Zhang and Huaiping Zhang for their kind proofreading of the manuscript. This work is supported by the National Natural Science Foundation of China under Grant 61231014.
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