Infrared Small Target Detection Based on Improved Tri-Layer Window Local Contrast

Due to the poor quality image with low signal-to-clutter ratio (SCR), infrared (IR) small target detection is faced with great challenges in the remote sensing field. Despite the fact that the local contrast measure (LCM) has been widely applied for IR target detection, the existing LCM-based methods suffer from weak target detectability (TD) or background suppressibility (BS) in complicate background. In this paper, we propose a novel IR small target detection method based on improved tri-layer window local contrast measure (TrLCM). With an additional isolation circle in TrLCM, the influence of background on target detection is reduced to a certain extent. Besides, background suppressibility is also promoted through a designed adaptive adjustment coefficient. Comprehensive experiments and analysis on three datasets verify that the proposed TrLCM achieves advanced TD, BS and overall performance.