基于超分辨率与在线检测DSST的红外小目标跟踪  

Infrared Small Target Tracking Based on Super-resolution and Online Detection DSST

作　　者：李斌 李秀红[1] 艾斯卡尔·艾木都拉[1] LI Bin;LI Xiuhong;Askar Hamdulla(College of Information Science and Engineering,Xinjiang University,Urumqi 830046,China)

机构地区：[1]新疆大学信息科学与工程学院,新疆乌鲁木齐830046

出　　处：《红外技术》2022年第7期659-666,共8页Infrared Technology

基　　金：新疆维吾尔自治区自然科学基金(2020D01C026);国家自然科学基金(61563049)。

摘　　要：红外小目标的相关研究在军事领域的制导、预警和边防间谍无人机检测中极其重要。针对红外小目标的跟踪研究,本文提出了一种基于超分辨率增强与在线检测DSST(Discriminative Scale Space Tracker)的小目标跟踪算法。首先,基于融入红外图像特征的超分辨率重建算法对原始图像进行更新,增强了弱小目标,然后,增强的图像被用作基于在线检测DSST算法的输入,得到响应映射,估计目标位置。实验结果表明,与几种最新算法相比,该算法在准确性方面表现出色。Research on infrared small targets is crucial in the areas of military guidance and early warning and detection of border spy UAVs. In this paper, a small target tracking algorithm based on super-resolution enhancement and online detection DSST is proposed for small target tracking research. First, the original image is updated based on the integrated infrared image features of the super-resolution reconstruction algorithm to enhance the dim target. In addition, the enhanced image is used as the input for the online detection DSST algorithm to perform response mapping and estimate the target position. The experimental results show that the accuracy of the proposed algorithm is high compared with those of several new algorithms.

关 键 词：小目标跟踪 超分辨率 DSST 在线检测 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]