Abstract
In the paper, the detection of IR weak and small targets is investigated in natural background based on fractal features. One feature of multi-scale variance ratio of fractal surface is proposed according to the fact that the fractal feature of man made objects changes shaper than the natural background. The new feature stands out the artificial objects much better from natural background than what can be done by fractal dimension feature or fractal model fit error feature, thus inhibiting background clutters well. Local gray histogram statistics is applied to object detection in the images with feature of multi-scale variance ratio of fractal surface. Experimental results shows that the detecting algorithm based on such a feature can localize weak and small objects stably in a single-frame image, and is a effective algorithm.
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© 2006 Springer-Verlag Berlin Heidelberg
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Zhang, H., Liu, X., Li, J., Zhenfu, Z. (2006). The Study of Detecting for IR Weak and Small Targets Based on Fractal Features. In: Cham, TJ., Cai, J., Dorai, C., Rajan, D., Chua, TS., Chia, LT. (eds) Advances in Multimedia Modeling. MMM 2007. Lecture Notes in Computer Science, vol 4352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69429-8_30
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DOI: https://doi.org/10.1007/978-3-540-69429-8_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69428-1
Online ISBN: 978-3-540-69429-8
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