Low-Rank and Sparse Decomposition Based Frame Difference Method for Small Infrared Target Detection in Coastal Surveillance

Weina ZHOU  Xiangyang XUE  Yun CHEN  

IEICE TRANSACTIONS on Information and Systems   Vol.E99-D   No.2   pp.554-557
Publication Date: 2016/02/01
Publicized: 2015/11/11
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2015EDL8186
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
target detection,  low-rank,  sparse recovery,  frame difference,  

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Detecting small infrared targets is a difficult but important task in highly cluttered coastal surveillance. The paper proposed a method called low-rank and sparse decomposition based frame difference to improve the detection performance of a surveillance system. First, the frame difference is used in adjacent frames to detect the candidate object regions which we are most interested in. Then we further exclude clutters by low-rank and sparse matrix recovery. Finally, the targets are extracted from the recovered target component by a local self-adaptive threshold. The experiment results show that, the method could effectively enhance the system's signal-to-clutter ratio gain and background suppression factor, and precisely extract target in highly cluttered coastal scene.