Subjective Quality Assessment of Thermal Infrared Images

Thermal infrared images (TIIs) can be distorted by multiple factors, resulting in noise, low contrast, limited dynamic range, and fuzziness, which greatly impede their usefulness. It is crucial to evaluate the quality of TIIs. Unfortunately, there have been very few attempts to study this problem. In this study, we collected 1,000 authentically distorted TIIs using thermal infrared acquisition equipment and conducted strict subjective experiments to obtain a thermal infrared image quality assessment (IQA) database. Each image’s quality score was obtained under strict scoring rules. Finally, we investigated the feasibility of several no-reference (NR) IQA methods in quality assessment of TIIs. We found that existing NR-IQA methods achieve ordinary performance in such a task, and there is an urgent need to develop a specific IQA methods for TIIs. The findings together with the constructed database are expected to pave the way for the development of more advanced IQA methods for further development of this field.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/icip51287.2024.10648145
Citations
3
Primary Topic
Infrared Target Detection Methodologies
Type
article
Field-Weighted Citation Impact
3.90

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article

Subjective Quality Assessment of Thermal Infrared Images

Yuanhao Gong, Tianwei Zhou, Guanghui Yue, Z. Xu et al.
3 citations
Infrared Target Detection Methodologies
3.90
article

Subjective Quality Assessment of Thermal Infrared Images

Yuanhao Gong, Tianwei Zhou, Guanghui Yue, Z. Xu, Wei Zhou, Shuigen Wang, Lixin Zhang, Jinxia Zhang
article en
3 citations

Abstract

Thermal infrared images (TIIs) can be distorted by multiple factors, resulting in noise, low contrast, limited dynamic range, and fuzziness, which greatly impede their usefulness. It is crucial to evaluate the quality of TIIs. Unfortunately, there have been very few attempts to study this problem. In this study, we collected 1,000 authentically distorted TIIs using thermal infrared acquisition equipment and conducted strict subjective experiments to obtain a thermal infrared image quality assessment (IQA) database. Each image’s quality score was obtained under strict scoring rules. Finally, we investigated the feasibility of several no-reference (NR) IQA methods in quality assessment of TIIs. We found that existing NR-IQA methods achieve ordinary performance in such a task, and there is an urgent need to develop a specific IQA methods for TIIs. The findings together with the constructed database are expected to pave the way for the development of more advanced IQA methods for further development of this field.

Shenzhen University (CN), Cardiff University (GB)
National Natural Science Foundation of China, Shenzhen University
Openalex Percentile: Top 6%
Infrared Target Detection Methodologies
3.90
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Subjective Quality Assessment of Thermal Infrared Images — Yuanhao Gong, Tianwei Zhou, et al. · (2024) | TGRS Research Map | TGRS