Journal
SIGNAL PROCESSING
Volume 217, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.sigpro.2023.109339
Keywords
Small target detection; Difference -of -structure tensors; Adaptive ring -shaped structural element; Fourier phase spectrum; Target awareness indicator
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This paper proposes a weighted adaptive ring top-hat transformation (WARTH) for extracting infrared small targets in complex backgrounds. The WARTH method effectively measures local and global feature information using an adaptive ring-shaped structural element and a target awareness indicator, resulting in accurate detection of small targets with minimized false alarms.
Complex background in infrared images often challenges the accurate detection of small targets. To address this problem, we propose a weighted adaptive ring top-hat transformation (WARTH) for extracting infrared small targets in complex backgrounds. The method utilizes an adaptive ring-shaped structural element (SE) and a target awareness indicator to effectively measure local and global feature information to detect small targets while minimizing false alarms accurately. Firstly, the difference-of-structure tensors (DoST) is designed, and the positive smallest eigenvalue of DoST (PSEDoST) is computed to construct the adaptive ring-shaped SE that captures local feature information for background estimation. Secondly, the image is converted into the Fourier phase spectrum, and a two-stage sliding window filtering technique is designed to generate the target awareness indicator that perceives global feature information of small targets. Finally, the WARTH is defined by fusing the above two measurements, which can further eliminate false alarms and improve the robustness of target detection. The experimental results demonstrate that the WARTH is superior to several advanced methods in terms of false alarm reduction and small target detection in complex backgrounds.
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