Machine Learning Based Image Quality Assessment Model
| Autor: | Li-Heng Chen, 陳立恆 |
|---|---|
| Rok vydání: | 2014 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 102 The objective image quality assessment (IQA) plays a key role in the development of various multimedia applications. The release of new IQA dataset (TID2013) challenges the wildly used 2D IQA metrics (e.g. PSNR and SSIM) since they cannot handle the diversity of distortion types. In this thesis, we propose a machine learning approach IQA model with features extracted from different frequency band (DOG features). The color distortion is also considered in our system. The effectiveness of our IQA system is verified by comparing with subjective score on the available databases. The experimental results show the high consistency between MOS score and our metric. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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