海面弱小目标红外检测算法的高速实现  

High speed implementation of infrared detection algorithm for dim maritime targets

作　　者：张雅楠[1] 陈绪光 许文海[1] ZHANG Ya-nan;CHEN Xu-guang;XU Wen-hai(College of Information Science and Technology,Dalian Maritime University,Dalian 116026,China)

机构地区：[1]大连海事大学信息科学技术学院

出　　处：《光电子．激光》2019年第5期516-521,共6页Journal of Optoelectronics·Laser

基　　金：国家科技支撑计划课题(2014BAB12B03)资助项目

摘　　要：为了实现红外图像中海面弱小目标的精确检测,提出了一种基于局部峰值检测和管道滤波的红外图像处理算法。首先采取局部峰值检测提取疑似目标,然后根据自适应域值处理去除多数非目标峰值,最后通过管道滤波法排除残留干扰以准确识别目标。针对算法中包括大量条件判断和并行计算的特点,通过比对CPU和GPU的工作特性,最终采用CPU-GPU协作的异构计算模型对算法进行了加速。实验结果表明,在大量海面杂波的干扰下,该加速检测算法运行后的目标检测漏警率不高于3.5%,虚警率不高于5%,加速比为26,处理分辨率为640X512图像的速率不低于32帧/秒,具有很高的工程应用价值。In order to realize the accurate detection of small dim target in the sea through infrared image, a detection algorithm based on local peak detection and pipeline-filtering are put forward by my team. The algorithm first extracts some suspected targets by local peak detection, and then removes most of the non-target peaks according to the self-adaptive threshold processing. Finally,the residual interference is eliminated by the pipeline filtering method to identify the target accurately. In view of the characteristics of the algorithm including a large number of conditions and parallel computing,this paper compares the work characteristics of CPU and GPU, and finally speeds up the algorithm by using the heterogeneous computing model of CPU-GPU collaboration. The experimental results show that the leakage alarm rate of the target detection is not higher than 3. 5 %, the false alarm rate is lower than 5%,the acceleration ratio is 26,the rate of resolution processing 640X512 images is not less than 32 frames per second, and it has high engineering application value.

关 键 词：红外图像 海面弱小目标 局部峰值检测 CPU和GPU高性能计算 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]