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Optical Engineering

Improved level-set framework-based algorithm for small infrared target detection
Author(s): Dengwei Wang; Tianxu Zhang; Luxin Yan; Xiaoyong Bian; Wenjun Shi
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Paper Abstract

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.

Paper Details

Date Published: 1 April 2011
PDF: 12 pages
Opt. Eng. 50(4) 047202 doi: 10.1117/1.3567056
Published in: Optical Engineering Volume 50, Issue 4
Show Author Affiliations
Dengwei Wang, Huazhong Univ. of Science and Technology (China)
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)
Luxin Yan, Huazhong Univ. of Science and Technology (China)
Xiaoyong Bian, Huazhong Univ. of Science and Technology (China)
Wenjun Shi, Navy Aeronautical and Astronautical Univ. (China)

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