Blind night-time image quality assessment : subjective and objective approaches
Blind image quality assessment (BIQA) aims to develop quantitative measures to automatically and accurately estimate the visual quality of an image without any prior information about its reference image. This issue has been attracting a great deal of attention for a long time; however, little work...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/154467 |
| _version_ | 1811681414084558848 |
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| author | Xiang, Tao Yang, Ying Guo, Shangwei |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Xiang, Tao Yang, Ying Guo, Shangwei |
| author_sort | Xiang, Tao |
| collection | NTU |
| description | Blind image quality assessment (BIQA) aims to develop quantitative measures to automatically and accurately estimate the visual quality of an image without any prior information about its reference image. This issue has been attracting a great deal of attention for a long time; however, little work has been done on night-time images, which are crucially important for consumer photography and practical applications such as automated driving systems. In this paper, to the best of our knowledge, we conduct the first exploration on subjective and objective quality assessment of night-time images. First, we build a large-scale natural night-time image database (NNID) containing 2240 images with 448 different image contents captured by different photographic equipment in real-world scenarios. Subsequently, we carry out a subjective experiment to evaluate the perceptual quality of all the images in the NNID database. Thereafter, we perform objective assessment of night-time images by proposing a blind night-time image quality assessment metric using brightness and texture features (BNBT). Finally, extensive experiments are conducted to evaluate the performance and efficiency of the proposed BNBT metric on the NNID database. The experimental results demonstrate that this metric outperforms existing state-of-the-art BIQA methods in terms of all evaluation criteria and has an acceptable computational cost at the same time. We have made the NNID database publicly available for downloading at https://sites.google.com/site/xiangtaooo/. |
| first_indexed | 2024-10-01T03:40:34Z |
| format | Journal Article |
| id | ntu-10356/154467 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:40:34Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1544672021-12-23T04:12:27Z Blind night-time image quality assessment : subjective and objective approaches Xiang, Tao Yang, Ying Guo, Shangwei School of Computer Science and Engineering Engineering::Computer science and engineering Blind Image Quality Assessment Natural Night-Time Images Blind image quality assessment (BIQA) aims to develop quantitative measures to automatically and accurately estimate the visual quality of an image without any prior information about its reference image. This issue has been attracting a great deal of attention for a long time; however, little work has been done on night-time images, which are crucially important for consumer photography and practical applications such as automated driving systems. In this paper, to the best of our knowledge, we conduct the first exploration on subjective and objective quality assessment of night-time images. First, we build a large-scale natural night-time image database (NNID) containing 2240 images with 448 different image contents captured by different photographic equipment in real-world scenarios. Subsequently, we carry out a subjective experiment to evaluate the perceptual quality of all the images in the NNID database. Thereafter, we perform objective assessment of night-time images by proposing a blind night-time image quality assessment metric using brightness and texture features (BNBT). Finally, extensive experiments are conducted to evaluate the performance and efficiency of the proposed BNBT metric on the NNID database. The experimental results demonstrate that this metric outperforms existing state-of-the-art BIQA methods in terms of all evaluation criteria and has an acceptable computational cost at the same time. We have made the NNID database publicly available for downloading at https://sites.google.com/site/xiangtaooo/. This work was supported by the National Natural Science Foundation of China under Grants 61672118 and 61932006. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Hantao Liu. 2021-12-23T04:12:27Z 2021-12-23T04:12:27Z 2020 Journal Article Xiang, T., Yang, Y. & Guo, S. (2020). Blind night-time image quality assessment : subjective and objective approaches. IEEE Transactions On Multimedia, 22(5), 1259-1272. https://dx.doi.org/10.1109/TMM.2019.2938612 1520-9210 https://hdl.handle.net/10356/154467 10.1109/TMM.2019.2938612 2-s2.0-85071775164 5 22 1259 1272 en IEEE Transactions on Multimedia © 2019 IEEE. All rights reserved. |
| spellingShingle | Engineering::Computer science and engineering Blind Image Quality Assessment Natural Night-Time Images Xiang, Tao Yang, Ying Guo, Shangwei Blind night-time image quality assessment : subjective and objective approaches |
| title | Blind night-time image quality assessment : subjective and objective approaches |
| title_full | Blind night-time image quality assessment : subjective and objective approaches |
| title_fullStr | Blind night-time image quality assessment : subjective and objective approaches |
| title_full_unstemmed | Blind night-time image quality assessment : subjective and objective approaches |
| title_short | Blind night-time image quality assessment : subjective and objective approaches |
| title_sort | blind night time image quality assessment subjective and objective approaches |
| topic | Engineering::Computer science and engineering Blind Image Quality Assessment Natural Night-Time Images |
| url | https://hdl.handle.net/10356/154467 |
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