Fast and robust small infrared target detection using absolute directional mean difference algorithm

• Published in: Signal processing Vol. 177; p. 107727
• Main Authors: Moradi, Saed, Moallem, Payman, Sabahi, Mohamad Farzan
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2020
• Subjects: Average absolute gray difference; Directional mean difference; Real-time implementation; Small infrared target detection; Structural background; Average absolute gray difference; Structural background; Real-time implementation; Small infrared target detection; Directional mean difference
• ISSN: 0165-1684; 1872-7557
• DOI: 10.1016/j.sigpro.2020.107727

•A fast and robust algorithm for small infrared target detection is proposed.•Directional approach is used to develop a novel algorithm called ADMD.•Both noise and background clutter are suppressed, effectively.•The proposed method is implemented in an efficient manner. Infrared small target detection in an infrared search and track (IRST) system is a challenging task. This situation becomes more complicated when high gray-intensity structural backgrounds appear in the field of view (FoV) of the infrared seeker. While the majority of the infrared small target detection algorithms neglect directional information, in this paper, a directional approach is presented to suppress structural backgrounds and develop a more effective detection algorithm. To this end, a similar concept to the average absolute gray difference (AAGD) is utilized to construct a novel directional small target detection algorithm called absolute directional mean difference (ADMD). Also, an efficient implementation procedure is presented for the proposed algorithm. The proposed algorithm effectively enhances the target area and eliminates background clutter. Simulation results on real infrared images prove the significant effectiveness of the proposed algorithm.