Photorealistic stylised image quality assessment database (PSIQAD) building and modelling
Image Quality Assessment (IQA) tasks have increasing importance in today’s context due to the ubiquitous use of imaging devices and image-editing applications. Despite having several existing IQA models, they usually evaluate the degradation or aesthetic aspect of an image. The emergence of Partiall...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/138132 |
| _version_ | 1826129384846655488 |
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| author | Low, Qing Ru |
| author2 | Lin Weisi |
| author_facet | Lin Weisi Low, Qing Ru |
| author_sort | Low, Qing Ru |
| collection | NTU |
| description | Image Quality Assessment (IQA) tasks have increasing importance in today’s context due to the ubiquitous use of imaging devices and image-editing applications. Despite having several existing IQA models, they usually evaluate the degradation or aesthetic aspect of an image. The emergence of Partially Artificial Images (PAIs), whose contents are partially or completely generated by image generation algorithms [39], brings more challenges to the applicability of conventional IQA methods since both enhancements and distortions exist in the generation process of PAIs. This project also discusses why conventional IQA metrics are unable to work for PAIs which mainly lies in the knowledge fed to build IQA metrics. A novel image database, Photorealistic Stylised Image Quality Assessment Database (PSIQAD), is introduced to analyse the human preference in photorealistic stylised images, a form of PAIs, with the creation of baseline objective Stylised IQA (SIQA) models to show how PSIQAD can be leveraged. The advantages of PSIQAD with respect to the existing databases were also reviewed. |
| first_indexed | 2024-10-01T07:39:43Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/138132 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:39:43Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1381322020-04-25T02:24:45Z Photorealistic stylised image quality assessment database (PSIQAD) building and modelling Low, Qing Ru Lin Weisi School of Computer Science and Engineering WSLin@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Image Quality Assessment (IQA) tasks have increasing importance in today’s context due to the ubiquitous use of imaging devices and image-editing applications. Despite having several existing IQA models, they usually evaluate the degradation or aesthetic aspect of an image. The emergence of Partially Artificial Images (PAIs), whose contents are partially or completely generated by image generation algorithms [39], brings more challenges to the applicability of conventional IQA methods since both enhancements and distortions exist in the generation process of PAIs. This project also discusses why conventional IQA metrics are unable to work for PAIs which mainly lies in the knowledge fed to build IQA metrics. A novel image database, Photorealistic Stylised Image Quality Assessment Database (PSIQAD), is introduced to analyse the human preference in photorealistic stylised images, a form of PAIs, with the creation of baseline objective Stylised IQA (SIQA) models to show how PSIQAD can be leveraged. The advantages of PSIQAD with respect to the existing databases were also reviewed. Bachelor of Engineering (Computer Science) 2020-04-25T02:24:45Z 2020-04-25T02:24:45Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/138132 en SCSE19-0162 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Low, Qing Ru Photorealistic stylised image quality assessment database (PSIQAD) building and modelling |
| title | Photorealistic stylised image quality assessment database (PSIQAD) building and modelling |
| title_full | Photorealistic stylised image quality assessment database (PSIQAD) building and modelling |
| title_fullStr | Photorealistic stylised image quality assessment database (PSIQAD) building and modelling |
| title_full_unstemmed | Photorealistic stylised image quality assessment database (PSIQAD) building and modelling |
| title_short | Photorealistic stylised image quality assessment database (PSIQAD) building and modelling |
| title_sort | photorealistic stylised image quality assessment database psiqad building and modelling |
| topic | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision |
| url | https://hdl.handle.net/10356/138132 |
| work_keys_str_mv | AT lowqingru photorealisticstylisedimagequalityassessmentdatabasepsiqadbuildingandmodelling |