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Low-SNR Infrared Point Target Detection and Tracking via Saliency-Guided Double-Stage Particle Filter
Low signal-to-noise ratio (SNR) infrared point target detection and tracking is crucial to study regarding infrared remote sensing. In the low-SNR images, the intensive noise will submerge targets. In this letter, a saliency-guided double-stage particle filter (SGDS-PF) formed by the searching parti...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9003241/ https://www.ncbi.nlm.nih.gov/pubmed/35408405 http://dx.doi.org/10.3390/s22072791 |
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author | Jia, Liangjie Rao, Peng Zhang, Yuke Su, Yueqi Chen, Xin |
author_facet | Jia, Liangjie Rao, Peng Zhang, Yuke Su, Yueqi Chen, Xin |
author_sort | Jia, Liangjie |
collection | PubMed |
description | Low signal-to-noise ratio (SNR) infrared point target detection and tracking is crucial to study regarding infrared remote sensing. In the low-SNR images, the intensive noise will submerge targets. In this letter, a saliency-guided double-stage particle filter (SGDS-PF) formed by the searching particle filter (PF) and tracking PF is proposed to detect and track targets. Before the searching PF, to suppress noise and enhance targets, the single-frame and multi-frame target accumulation methods are introduced. Besides, the likelihood estimation filter and image block segmentation are proposed to extract the likelihood saliency and obtain proper proposal density. Guided by this proposal density, the searching PF detects potential targets efficiently. Then, with the result of the searching PF, the tracking PF is adopted to track and confirm the potential targets. Finally, the path of the real targets will be output. Compared with the existing methods, the SGDS-PF optimizes the proposal density for low-SNR images. Using a few accurate particles, the searching PF detects potential targets quickly and accurately. In addition, initialized by the searching PF, the tracking PF can keep tracking targets using very few particles even under intensive noise. Furthermore, the parameters have been selected appropriately through experiments. Extensive experimental results show that the SGDS-PF has an outstanding performance in tracking precision, tracking reliability, and time consumption. The SGDS-PF outperforms the other advanced methods. |
format | Online Article Text |
id | pubmed-9003241 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90032412022-04-13 Low-SNR Infrared Point Target Detection and Tracking via Saliency-Guided Double-Stage Particle Filter Jia, Liangjie Rao, Peng Zhang, Yuke Su, Yueqi Chen, Xin Sensors (Basel) Article Low signal-to-noise ratio (SNR) infrared point target detection and tracking is crucial to study regarding infrared remote sensing. In the low-SNR images, the intensive noise will submerge targets. In this letter, a saliency-guided double-stage particle filter (SGDS-PF) formed by the searching particle filter (PF) and tracking PF is proposed to detect and track targets. Before the searching PF, to suppress noise and enhance targets, the single-frame and multi-frame target accumulation methods are introduced. Besides, the likelihood estimation filter and image block segmentation are proposed to extract the likelihood saliency and obtain proper proposal density. Guided by this proposal density, the searching PF detects potential targets efficiently. Then, with the result of the searching PF, the tracking PF is adopted to track and confirm the potential targets. Finally, the path of the real targets will be output. Compared with the existing methods, the SGDS-PF optimizes the proposal density for low-SNR images. Using a few accurate particles, the searching PF detects potential targets quickly and accurately. In addition, initialized by the searching PF, the tracking PF can keep tracking targets using very few particles even under intensive noise. Furthermore, the parameters have been selected appropriately through experiments. Extensive experimental results show that the SGDS-PF has an outstanding performance in tracking precision, tracking reliability, and time consumption. The SGDS-PF outperforms the other advanced methods. MDPI 2022-04-05 /pmc/articles/PMC9003241/ /pubmed/35408405 http://dx.doi.org/10.3390/s22072791 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jia, Liangjie Rao, Peng Zhang, Yuke Su, Yueqi Chen, Xin Low-SNR Infrared Point Target Detection and Tracking via Saliency-Guided Double-Stage Particle Filter |
title | Low-SNR Infrared Point Target Detection and Tracking via Saliency-Guided Double-Stage Particle Filter |
title_full | Low-SNR Infrared Point Target Detection and Tracking via Saliency-Guided Double-Stage Particle Filter |
title_fullStr | Low-SNR Infrared Point Target Detection and Tracking via Saliency-Guided Double-Stage Particle Filter |
title_full_unstemmed | Low-SNR Infrared Point Target Detection and Tracking via Saliency-Guided Double-Stage Particle Filter |
title_short | Low-SNR Infrared Point Target Detection and Tracking via Saliency-Guided Double-Stage Particle Filter |
title_sort | low-snr infrared point target detection and tracking via saliency-guided double-stage particle filter |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9003241/ https://www.ncbi.nlm.nih.gov/pubmed/35408405 http://dx.doi.org/10.3390/s22072791 |
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