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https://open.uns.ac.rs/handle/123456789/3159
Title: | Blind DIBR-synthesized image quality assessment based on sparsity features in morphological multiscale domain | Authors: | Bokan, Dejan Velikić G. Kukolj, Dragan Sandić-Stanković D. |
Issue Date: | 30-Jun-2017 | Journal: | 2017 9th International Conference on Quality of Multimedia Experience, QoMEX 2017 | Abstract: | © 2017 IEEE. In this paper a no-reference image quality assessment (IQA) metric for DIBR-synthesized images is proposed. Sparsity based features of morphologically decomposed image subbands are used to estimate distortion level in images. A General regression neural network is utilized to calculate quality score. The performance is evaluated using publicly available IRCCyN/IVC DIBR image database. Experimental results show that proposed metric accords with human subjective judgment. | URI: | https://open.uns.ac.rs/handle/123456789/3159 | ISBN: | 9781538640241 | DOI: | 10.1109/QoMEX.2017.7965645 |
Appears in Collections: | FTN Publikacije/Publications |
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