An algorithm for multi-target detection in multi-temporal remote sensing images

doi:10.7523/j.issn.2095-6134.2021.04.009

Abstract

Abstract: With the rapid development of remote sensing technology, the remote sensing data become valuable in many practical applications. Among them, target detection has always been an important topic. However, most of the target detection algorithms in remote sensing images merely concentrate on single-temporal data, and there are few algorithms for multi-temporal data. In the field of target detection in multi-temporal remote sensing data, filter tensor analysis (FTA) has achieved great success which outperforms other target detection algorithms for single-temporal data. Yet FTA is designed only for single target detection, which means it can not meet the need for practical applications in circumstances where it has to detect more than one target simultaneously. So, in this paper, a modified algorithm for multi-target detection in multi-temporal data has been proposed based on the target constraints in multiple target constrained energy minimization and the tensor filter in FTA. Both the experiment results on simulation data and real remote sensing data from Landsat 8 prove that the algorithm proposed in this paper can effectively detect several targets in multi-temporal data.

Key words: multi-target detection, multi-temporal, filter tensor analysis, constrained energy minimization, remote sensing data

CLC Number:

TP753

XI Yanxin, JI Luyan, GENG Xiurui. An algorithm for multi-target detection in multi-temporal remote sensing images[J]. Journal of University of Chinese Academy of Sciences, 2021, 38(4): 503-510.

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