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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lu, Z. Yang, X.K. Lin, W.S. Ong, E.P. Yao, S. |
| Copyright Year | 2004 |
| Description | Author affiliation: Agency for Sci., Technol. & Res., Inst. for Infocomm Res., Singapore (Lu, Z.; Yang, X.K.; Lin, W.S.; Ong, E.P.; Yao, S.) |
| Abstract | The perceptual visual quality evaluation of Human Visual System (HVS) is very complex. It concerns almost all aspects of visual processing in vision path, from low-level neuron activities to high-level visual perception. Existing perceptual Visual Quality Metrics (VQMs) only considered several of the mechanisms of HVS and many others are ignored. In this paper, two global modulatory factors, visual attention and motion suppression, are modelled and combined to form a mathematic expression - Perceptual Quality Significant Level (PQSL). To a certain extent, it is believed that PQSL value reflect the processing ability of human brain on local visual contents. To evaluate their effects on visual quality evaluation, two VQMs are proposed. One is a MSE-like VQM based on PQSL-modulated JND profile, which was proposed in Z.K. Lu et al., (2004); the other VQM is based on Wang's visual quality assessment Zhou Wang et al., (2004) PQSL values are used to adjust the weights of his structural similarity index. Experimental results show that introducing of the global modulatory factors can improve the performance of current visual quality metrics. |
| Starting Page | 2311 |
| Ending Page | 2314 |
| File Size | 319557 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780385543 |
| ISSN | 15224880 |
| DOI | 10.1109/ICIP.2004.1421562 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-10-24 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Humans Distortion measurement Visual perception Psychology Noise measurement Neurons Quality assessment Layout Object recognition Decoding |
| Content Type | Text |
| Resource Type | Article |
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