Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/1024| Title: | Blind DIBR-synthesized Image Quality Assessment using multi-scale DoG and GRNN | Authors: | Sandic-Stankovic D. Bokan, Dejan Kukolj, Dragan |
Issue Date: | 21-Dec-2018 | Journal: | 2018 14th Symposium on Neural Networks and Applications, NEUREL 2018 | Abstract: | © 2018 IEEE. In this paper, we explore the suitability of multi-resolution and multi-scale band-pass image representation generated by difference of Gaussian (DoG) operator for blind image quality assessment model. The developed model is based on general regression neural network (GRNN). The proposed model is consistent with human perception when evaluated on DIBR-synthesized image dataset. | URI: | https://open.uns.ac.rs/handle/123456789/1024 | ISBN: | 9781538669747 | DOI: | 10.1109/NEUREL.2018.8587020 |
| Appears in Collections: | FTN Publikacije/Publications |
Show full item record
SCOPUSTM
Citations
2
checked on May 3, 2024
Page view(s)
30
Last Week
1
1
Last month
6
6
checked on May 10, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.