基于局部对比度与方向导数的抗诱饵红外小目标检测算法OA

Infrared small target detection technology holds significant application value in urban se-curity,remote sensing surveying,and military guidance,but the combined interference from natu-ral background clutter and artificial decoy flares severely degrades its detection accuracy and ro-bustness.To address this issue,this paper presents an anti-decoy infrared small target detection algorithm integrating local contrast and directional derivative features.The proposed method first extracts local contrast reflecting spatial distribution characteristics and second-order directional de-rivative capturing edge structure features,then adaptively fuses these features to suppress back-ground clutter and decoy interference while extracting small targets.To handle decoy occlusion scenarios,a feature mutation discrimination mechanism is introduced by calculating inter-frame feature differences to identify occlusion events,during which the Kalman filter predicts target po-sitions to maintain detection continuity.After decoy separation,rapid target recapture is achieved.Comparative experiments on real-world infrared sequences with decoy interference demonstrate that the algorithm effectively suppresses complex backgrounds and decoys while achieving high de-tection accuracy and robustness.