低空复杂场景红外弱小目标快速精准检测

针对低空复杂场景下红外弱小动目标检测难度大、虚警率高等问题,面向探测系统中高帧频图像实时处理应用需求,提出基于全卷积网络的弱小目标精准检测方法和基于现场可编程逻辑门阵列(field programmable gate array, FPGA)的低时延并行处理方法。采用轻量化全卷积网络对红外图像中弱小目标进行空域检测,对相邻图像帧疑似目标进行时域轨迹关联以进一步降低虚警率。实验结果表明:上述方法相比于五种传统方法在检测率和虚警率性能方面均有显著提升,并在单片FPGA上完成100 Hz图像实时处理,处理时延低于1.8 ms,实现低空复杂场景弱小目标高精度高鲁棒快速实时检测。

Fast and accurate detection of infrared dim small target in low altitude complex scenes

Aiming at the high difficulty and high false alarm rate of infrared dim small moving target detection in low altitude and complex scenes, a precise detection method based on full convolution network and a low-latency parallel processing method based on FPGA (field programmable gate array) were proposed to meet the real-time processing application requirements of high frame rate images in the detection system. A lightweight full convolutional network was used to detect dim small targets in spatial domain, and time domain trajectory correlation on suspected targets in adjacent frames was performed to further reduce false alarms. The experimental results show that the detection rate and false alarm rate are significantly improved compared with the five traditional methods. And the real-time processing of 100 Hz image is completed on a single FPGA with the processing delay less than 1.8 ms. This method realizes high-precision, high-robust and fast real-time detection of dim small targets in complex low altitude scene.