@InProceedings{RafaelE.Rivadeneira2023,
author="Rafael E. Rivadeneira
and Henry Velesaca
and Angel Sappa",
title="Object Detection in Very Low-Resolution Thermal Images through a Guided-Based Super-Resolution Approach",
booktitle="17th International Conference on Signal-Image Technology \& Internet-Based Systems",
year="2023",
abstract="This work proposes a novel approach that integrates super-resolution techniques with off-the-shelf object detection methods to tackle the problem of handling very low-resolution thermal images. The suggested approach begins by enhancing the low-resolution (LR) thermal images through a guided super-resolution strategy, leveraging a high-resolution (HR) visible spectrum image. Subsequently, object detection is performed on the high-resolution thermal image. The experimental results demonstrate tremendous improvements in comparison with both scenarios: when object detection is performed on the LR thermal image alone, as well as when object detection is conducted on the up-sampled LR thermal image. Moreover, the proposed approach proves highly valuable in camouflaged scenarios where objects might remain undetected in visible spectrum images.",
optnote="MSIAU",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=4010), last updated on Mon, 10 Jun 2024 12:21:22 +0200",
doi="10.1109/SITIS61268.2023.00056",
opturl="https://ieeexplore.ieee.org/document/10472816"
}