No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics
High dynamic range omnidirectional image (HOI) can provide more real and immersive watching experience for viewers, thus has become an important presentation of virtual reality technology. However, both the system processing and the characteristics of HOI make the design of HOI quality metric (HOIQM...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | IET Signal Processing |
| Online Access: | http://dx.doi.org/10.1049/2024/5653845 |
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| _version_ | 1849409741613170688 |
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| author | Rongyao Yu Fang Yang Yi Liu Jianghui He Qingjiang Pang Yang Song |
| author_facet | Rongyao Yu Fang Yang Yi Liu Jianghui He Qingjiang Pang Yang Song |
| author_sort | Rongyao Yu |
| collection | DOAJ |
| description | High dynamic range omnidirectional image (HOI) can provide more real and immersive watching experience for viewers, thus has become an important presentation of virtual reality technology. However, both the system processing and the characteristics of HOI make the design of HOI quality metric (HOIQM) a challenging issue. In this work, considering the difference between whole field of view (FoV) and viewer-selected viewport, distortion features from both global and local perspectives are extracted, and a blind HOIQM is proposed. Specifically, because different regions have different projections in SSP projection, we have constructed the optimal bivariate response pair in the equatorial region and bipolar region according to their projection direction, and parameters in the BGGD based-spatial oriented correlation model are extracted as global statistical features. Meanwhile, combined with the visual perception for HOI, the key blocks are determined in equatorial region, and the local statistical characteristics of the key blocks are extracted by analyzing the distribution of multiscale structure information. Finally, the global and local features are regressed by SVR to obtain the final HOI quality. Experimental results on NBU-HOID database demonstrate that the proposed quality metric is outperformed the existing representative quality metrics and is more consistent with human visual perception for HOI. |
| format | Article |
| id | doaj-art-7da4f555659842e1a19d45e192014c9b |
| institution | Kabale University |
| issn | 1751-9683 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Signal Processing |
| spelling | doaj-art-7da4f555659842e1a19d45e192014c9b2025-08-20T03:35:24ZengWileyIET Signal Processing1751-96832024-01-01202410.1049/2024/5653845No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical CharacteristicsRongyao Yu0Fang Yang1Yi Liu2Jianghui He3Qingjiang Pang4Yang Song5Ningbo No. 2 HospitalHealth Science CenterCollege of Science and TechnologyFaculty of Electronic Engineering and Computer ScienceNingbo No. 2 HospitalCollege of Science and TechnologyHigh dynamic range omnidirectional image (HOI) can provide more real and immersive watching experience for viewers, thus has become an important presentation of virtual reality technology. However, both the system processing and the characteristics of HOI make the design of HOI quality metric (HOIQM) a challenging issue. In this work, considering the difference between whole field of view (FoV) and viewer-selected viewport, distortion features from both global and local perspectives are extracted, and a blind HOIQM is proposed. Specifically, because different regions have different projections in SSP projection, we have constructed the optimal bivariate response pair in the equatorial region and bipolar region according to their projection direction, and parameters in the BGGD based-spatial oriented correlation model are extracted as global statistical features. Meanwhile, combined with the visual perception for HOI, the key blocks are determined in equatorial region, and the local statistical characteristics of the key blocks are extracted by analyzing the distribution of multiscale structure information. Finally, the global and local features are regressed by SVR to obtain the final HOI quality. Experimental results on NBU-HOID database demonstrate that the proposed quality metric is outperformed the existing representative quality metrics and is more consistent with human visual perception for HOI.http://dx.doi.org/10.1049/2024/5653845 |
| spellingShingle | Rongyao Yu Fang Yang Yi Liu Jianghui He Qingjiang Pang Yang Song No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics IET Signal Processing |
| title | No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics |
| title_full | No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics |
| title_fullStr | No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics |
| title_full_unstemmed | No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics |
| title_short | No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics |
| title_sort | no reference high dynamic range omnidirectional image quality metric from the perspective of global and local statistical characteristics |
| url | http://dx.doi.org/10.1049/2024/5653845 |
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