采用扩展MRF的红外目标自适应检测方法

针对天基红外监视系统中不同形状目标的联合检测问题，提出基于扩展马尔可夫随机场的自适应目标检测算法。首先分析了天基红外监视系统中的目标特性，在此基础上以典型目标形状为模板，构建了扩展的马尔可夫随机场邻域系统；其次构建了新的马尔可夫势函数，并利用红外图像中背景与目标之间的马尔可夫势差异，将复杂背景中不同形状目标联合检测问题转换为马尔可夫势差异的判别问题，有效解决了马尔可夫随机场理论框架下混合形状目标检测问题。仿真试验结果表明，所提出的算法能够根据目标形状的变化自适应地检测各类目标，并可在不同图像信杂比条件下进行目标检测处理，具有较强的鲁棒性。

Adaptive detection method for infrared target using extended MRF

Aiming at the problem of combination detection of targets with various shapes in space based infrared surveillance system, an adaptive target detection method based on extended Markov random field (E-MRF) was proposed. First, the target characteristics in space based infrared surveillance system were analyzed and the extended MRF neighborhood system was established by using the typical target shapes as templates. Then the new MRF potential function was constructed. By using the potential differences between the infrared background and target, the detection problem of targets with various shapes under complex background was formulated as a discrimination problem of MRF potential function and finally the problem of mixed shape targets detection under MRF theory framework was efficiently solved. Simulation and experimental results show that the proposed method can adaptively adjust the operator according to the target shapes and perfectly detect targets with different shapes under various image SCRs. So the proposed method has a stabile performance.