‍YANG Degui,HAN Tonghuan,HU Liang,et al. Research status and prospect of single frame infrared dim small target detection technology[J]. Journal of Signal Processing, 2024,40(5): 887-906. DOI: 10.16798/j.issn.1003-0530.2024.05.008
Citation: ‍YANG Degui,HAN Tonghuan,HU Liang,et al. Research status and prospect of single frame infrared dim small target detection technology[J]. Journal of Signal Processing, 2024,40(5): 887-906. DOI: 10.16798/j.issn.1003-0530.2024.05.008

Research Status and Prospect of Single Frame Infrared Dim Small Target Detection Technology

  • ‍ ‍Infrared detection technology has been widely applied in fields such as space-based early warning and terminal seeker guidance systems due to its advantages of long detection distance, strong anti-interference ability, high concealment, and all-weather capability. Through infrared imaging technology, target images can be obtained. Thus, targets can be alerted, identified, and tracked. In practical scenarios, target images often occupy a small proportion of pixels, have low signal strength, and are easily overwhelmed by background images. Background images undergo drastic changes and possess strong structural information, edges, and noise. Infrared images have a low signal-to-noise ratio, making target detection challenging. This has always been a research difficulty and a hot topic in the field of target detection.Numerous algorithms have been proposed to improve the detection capability of small and weak targets in infrared images. Existing mainstream detection methods are classified into single-frame detection and multi-frame detection based on the method of image data detection. Multi-frame algorithms rely on a large amount of image data support, have long response cycles, and have low application potential. Conversely, single-frame detection algorithms are widely used in high-speed moving target detection, early warning systems, and other fields due to their low complexity, strong timeliness, and ease of hardware implementation.Therefore, this study focuses on single-frame infrared weak target detection algorithms and elaborates on the principles and recent typical applications of four categories of algorithms: filtering-based, contrast and saliency analysis-based, data optimization-based, and deep learning-based. Through simulation experiments and algorithm complexity comparisons, the performance, advantages, and limitations of different algorithms are summarized. The research status of weak target detection algorithms is summarized, and the future development trends in this field are discussed. The work presented in this paper can help readers quickly understand the research status in this field and provide references for researchers.
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