1 April 2011 Improved level-set framework-based algorithm for small infrared target detection
Author Affiliations +
Optical Engineering, 50(4), 047202 (2011). doi:10.1117/1.3567056
An improved algorithm integrating wavelet decomposition, multilevel filtering, and an additive operator splitting (AOS)-based level-set framework for infrared small target detection is proposed. This model has two components: a filtering operation, and level-set evolution. In the filtering step, the original image is first decomposed using a wavelet transform. After determining the location of sea-sky line, we construct a subimage based on the sea-sky-line position, and then execute multilevel filtering on this subimage. This filtering framework provides the input image for the level-set evolution. Using the level-set formulation, complex curves can be detected while naturally handling topological changes of the evolving curves. To reduce the computational cost required by an explicit implementation of the level-set formulation, a new solver named AOS is proposed. Additionally, the quantitative analyses for our algorithm are also given. Experiments on real infrared image sequences indicate that our method is efficient and robust.
Dengwei Wang, Tianxu Zhang, Luxin Yan, Xiaoyong Bian, Wenjun Shi, "Improved level-set framework-based algorithm for small infrared target detection," Optical Engineering 50(4), 047202 (1 April 2011). https://doi.org/10.1117/1.3567056


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