Data · dataset · 2024
A dataset of semi-synthetic detection for small infrared moving targets under complex backgrounds
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Small infrared moving target detection is one of the key technologies of infrared detection.
Description
And it has always been a hot issue in photoelectric detection, especially for small infrared moving target under clutter background. The problem has not yet been solved.
In view of the lack of high quality data in current research, we adopt infrared imaging equipment installed on a small UAV platform to capture image sequences as backgrounds. The synthetic targets are embedded in backgrounds properly. We build a semi-synthetic dataset for small infrared moving target detection under clutter background.
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Various conditions are set in image capturing, including relative height (up looking, head up looking and down looking), scenes (vegetation, water and building), platform motion, weather, time, etc. The imaging platform motion and the synthetic target motion are considered simultaneously to guarantee that the semi-synthetic image sequences as close as possible to the real application scenario. In addition, we vary the target characteristics in synthetizing, including shape, intensity, and motion.
Our dataset contains 350 image sequences, 150185 images. The annotation file provided the targets positions in images. The dataset can be used in small infrared moving target detection and tracking researches.If you use our dataset, please cite our three related papers:[1].
L. Guo, X. Sun, W. Zhang, Z. Li and Q. Yu, "Small Aerial Target Detection Using Trajectory Hypothesis and Verification," in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-14, 2023, Art no. 5609314, doi: 10.1109/TGRS.2023.3271725.[2]. X. Sun, L. Guo, W. Zhang, Z. Wang and Q. Yu, "Small Aerial Target Detection for Airborne Infrared Detection Systems Using LightGBM and Trajectory Constraints," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 9959-9973, 2021, doi: 10.1109/JSTARS.2021.3115637.[3].
Sun Xiaoliang, Guo Liangchao, Zhang Wenlong, Wang Zi, Hou Yanjie, Li Zhang, Teng Xichao. A dataset of semi-synthetic detection for small infrared moving targets under complex backgrounds[J/OL]. Chinese Scientific Data, 2024, 9(3).
(2024-09-23). DOI: 10.11922/csdata.2021.0015.zh.Besides, in the latest version, we newly submitted three files: train_anno_update.json, test_anno_update.json and validation.py. train_anno_update.json and test_anno_update.json are the updated ground truth annotation files with target signal-to-noise ratio data added. validation.py is used for verifying the detection results.
Links
Where it is published
- DOI doi.org/10.11922/sciencedb.j00001.00231 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.11922%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Image 75% · Imaging 75% · Satellite remote sensing 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.11922/sciencedb.j00001.00231 | 9 d ago | JSON v1 |
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| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |