Research Article
Detection of Moving Infrared Small Target Based on Fusion of Multi-gradient Filter and Vibe Algorithm
@INPROCEEDINGS{10.1007/978-3-030-72795-6_48, author={Guofeng Zhang and Askar Hamdulla}, title={Detection of Moving Infrared Small Target Based on Fusion of Multi-gradient Filter and Vibe Algorithm}, proceedings={Simulation Tools and Techniques. 12th EAI International Conference, SIMUtools 2020, Guiyang, China, August 28-29, 2020, Proceedings, Part II}, proceedings_a={SIMUTOOLS PART 2}, year={2021}, month={4}, keywords={Vibe algorithm Ghost Gradient filter Image fusion}, doi={10.1007/978-3-030-72795-6_48} }- Guofeng Zhang
Askar Hamdulla
Year: 2021
Detection of Moving Infrared Small Target Based on Fusion of Multi-gradient Filter and Vibe Algorithm
SIMUTOOLS PART 2
Springer
DOI: 10.1007/978-3-030-72795-6_48
Abstract
Aiming at the problem that dim small targets are submerged to complicated background in infrared images, it is difficult to complete extraction from background and noise clutter. An improved vibe algorithm is proposed for small target detection and tracking. First, target areas are extracted and stored by using vibe algorithm in every frame of video, meanwhile local multi-gradient filter is used to detect and store prominent edge information in each same frame of video. Then, fusion image is obtained through vibe algorithm and multi-gradient filter. Finally, a threshold separation technique is used to further eliminate background clutter and extract small targets. The experimental results show that proposed algorithm can quickly eliminate ghosts and is effective for detecting moving small targets. Compare to other background difference method, gaussian mixture model, experimental evaluation results show that our method outperforms vibe, background difference method and gaussian mixture model methods in terms of both tracking accuracy and computation speed for detection infrared small targets.
