Infrared small-target detection via tensor construction and decomposition

Zhenguo Chen, Shuizhong Chen, Zhengjun Zhai*, Mingjing Zhao, Feiran Jie, Wei Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Infrared small-target detection of a low signal-to-noise ratio (SNR) has been an important research hotspot. Small targets lack texture and detailed information; in addition, the background tends to be complex and diverse. These factors mean small targets can be easily submerged, resulting in a low probability of detection and a high false alarm rate. In the absence of texture and detailed information in infrared images, neighbouring spatial information is a good complement. In this paper, a novel method is proposed, which introduces three-order tensor construction and decomposition (TCD) to fully utilize neighbouring spatial information. Furthermore, discontinuous multi-scale windows are designed to achieve a more robust detection performance. Experiments are performed on three real infrared datasets and the results demonstrate the effectiveness of the proposed TCD.

Original languageEnglish
Pages (from-to)900-909
Number of pages10
JournalRemote Sensing Letters
Volume12
Issue number9
DOIs
Publication statusPublished - 2021

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