基于全变分理论的红外图像背景抑制

Infrared Background Clutter Suppression Based on Total Variation Theory

针对红外单帧图像的小目标检测问题,提出基于全变分理论的背景杂波抑制的改进算法。构建以能量函数极值最优化为主体的全变分模型,结合自适应步长和非单调性线搜索条件,形成改进的全变分算法,在红外图像背景抑制方面取得良好效果。经过仿真实验测试几种算法的抑制效能,分析结果表明改进算法的检测性能较传统算法在杂波抑制、减少边缘虚警等方面均有优势,能够满足实时性要求,且适用于复杂背景的工程实现。

An improved algorithm of background clutter suppression based on total variation theory is proposed for infrared small target detection in a single frame image under complicated background. Combined with adaptive step size and non-monotone line search condition, the improved model whose main body is an optimization problem of energy function can achieve good results for background clutter suppression of infrared image. The simulation results about inhibition efficiency show that such method is remarkably improved compared with traditional methods in cluttering suppression and reducing false-alarm on edges. It can not only satisfy real-time requirement, but also its implementation is suitable for engineering fulfillment of infrared image under complicated background.