基于多特征的快速红外弱小目标检测算法

为了从全向红外搜索和跟踪系统采集的海量大视场高分辨率红外图像中快速准确地检测出红外弱小目标,本文提出了一种基于由粗到细的分阶段检测策略和时空域特征融合的红外弱小目标检测算法.首先,通过引入基于频域的快速显著性检测算法预先检测出目标可能存在的候选区域;其次,对候选区域进行角点检测以判定是否存在候选目标;最后,通过结合帧间时空域特征对候选目标进行进一步判定,以提取真实目标、删除虚假目标.多种实际场景的实验结果表明,该目标检测算法不仅运算量小而且探测概率高、虚警率低,是一种工程实用性能很好的红外弱小目标检测算法.

Fast Infrared and Dim Target Detection Algorithm Based on Multi-feature

In order to detect dim infrared targets from a mass of high resolution images in wide field of view system rapidly and accurately, a novel target detection method based on a phased strategy for research and multi-feature fusion is proposed in this paper.First of all, a saliency detection algorithm based on frequency-domain is carried out to extract candidate region which may contain targets.Then, invariant corner detection algorithm is adopted in candidate region to determine the presence of suspicious targets.Finally, the real targets can be confirmed by time-space coherence in multi frames.The experiment proves that the proposed method can detect dim infrared targets with small calculating amount, high detection probability and low false alarm rate.It is suitable for Infrared Search and Track system in practical engineering.