In this paper, the temporal different characteristics between the target and background pixels are used to detect dim moving targets in the slow-evolving complex background. A local and global variance filter on tempo...In this paper, the temporal different characteristics between the target and background pixels are used to detect dim moving targets in the slow-evolving complex background. A local and global variance filter on temporal profiles is presented that addresses the temporal characteristics of the target and background pixels to eliminate the large variation of background temporal profiles. Firstly, the temporal behaviors of different types of image pixels of practical infrared scenes are analyzed.Then, the new local and global variance filter is proposed. The baseline of the fluctuation level of background temporal profiles is obtained by using the local and global variance filter. The height of the target pulse signal is extracted by subtracting the baseline from the original temporal profiles. Finally, a new target detection criterion is designed. The proposed method is applied to detect dim and small targets in practical infrared sequence images. The experimental results show that the proposed algorithm has good detection performance for dim moving small targets in the complex background.展开更多
This paper describes a new method of small moving target detection and analyzes the performance of this algorithm. The method is based on multi-level threshold decision-making and sliding trajectory confidence testing...This paper describes a new method of small moving target detection and analyzes the performance of this algorithm. The method is based on multi-level threshold decision-making and sliding trajectory confidence testing technology. The parameters of the algorithm are also given. Experiments have been conducted, the results show that the algorithm has advantages of high detection probability, simple structure, and excellent real-time performance.展开更多
基金National Natural Science Foundation of China(61774120)
文摘In this paper, the temporal different characteristics between the target and background pixels are used to detect dim moving targets in the slow-evolving complex background. A local and global variance filter on temporal profiles is presented that addresses the temporal characteristics of the target and background pixels to eliminate the large variation of background temporal profiles. Firstly, the temporal behaviors of different types of image pixels of practical infrared scenes are analyzed.Then, the new local and global variance filter is proposed. The baseline of the fluctuation level of background temporal profiles is obtained by using the local and global variance filter. The height of the target pulse signal is extracted by subtracting the baseline from the original temporal profiles. Finally, a new target detection criterion is designed. The proposed method is applied to detect dim and small targets in practical infrared sequence images. The experimental results show that the proposed algorithm has good detection performance for dim moving small targets in the complex background.
文摘This paper describes a new method of small moving target detection and analyzes the performance of this algorithm. The method is based on multi-level threshold decision-making and sliding trajectory confidence testing technology. The parameters of the algorithm are also given. Experiments have been conducted, the results show that the algorithm has advantages of high detection probability, simple structure, and excellent real-time performance.
