Infrared small target detection based on non-subsampled shearlet transform and phase spectrum of quaternion Fourier transform

Infrared small target detection is a crucial part of infrared search and track system, and it has been a significant research topic in the past decades. Inspired by previous studies showing that phase spectrum of quaternion Fourier transform (PQFT) great superiority in salient region extraction and...

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Bibliographic Details
Published in:Optical and quantum electronics 2020-03, Vol.52 (3), Article 168
Main Authors: Ren, Kan, Song, Congcong, Miao, Xin, Wan, Minjie, Xiao, Junfeng, Gu, Guohua, Chen, Qian
Format: Article
Language:English
Subjects:
Characterization and Evaluation of Materials
Computer Communication Networks
Decomposition
Electrical Engineering
Fourier transforms
High frequencies
Infrared tracking
Lasers
Optical Devices
Optics
Phase transitions
Photonics
Physics
Physics and Astronomy
Quaternions
Shearing
Target detection
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Summary:Infrared small target detection is a crucial part of infrared search and track system, and it has been a significant research topic in the past decades. Inspired by previous studies showing that phase spectrum of quaternion Fourier transform (PQFT) great superiority in salient region extraction and the desirable characteristics of multi-scale, multi-direction and shift-invariant with non-subsampled shearlet transform (NSST), a new target detection method is proposed based on NSST and PQFT in this paper. The original image is first subjected to NSST decomposition to obtain a low frequency component and four high frequency components by NSP. Next, directional localization is achieved by shearing filters which provides multi-directional decomposition. Then, four direction high frequency sub-images decomposed by NSST are introduced as four data channels of PQFT. The reconstruction map that highlights the salient region in the time domain is computed using the inverse PQFT. Lastly, the real target is directly segmented by an adaptive threshold. The proposed method is validated by five test sequences. The experimental results show that our method is superior to other traditional methods in terms of robustness and effectiveness in complex background.
ISSN:0306-8919
1572-817X
DOI:10.1007/s11082-020-02292-x