Abstract
Monitoring and controlling the user's perceived quality, in modern video services is a challenging proposition, mainly due to the limitations of current Image Quality Assessment (IQA) algorithms. Subjective Quality of Experience (QoE) is widely used to get a right impression, but unfortunately this can not be used in real world scenarios. In general, objective QoE algorithms represent a good substitution for the subjective ones, and they are split in three main directions: Full Reference (FR), Reduced Reference (RR), and No Reference (NR). From these three, the RR IQA approach offers a practical solution to assess the quality of an impaired image due to the fact that just a small amount of information is needed from the original image. At the same time, keeping in mind that we need automated QoE algorithms which are context independent, in this paper we introduce a novel stochastic RR IQA metric to assess the quality of an image based on Deep Learning, namely Restricted Boltzmann Machine Similarity Measure (RBMSim). RBMSim was evaluated on two benchmarked image databases with subjective studies, against objective IQA algorithms. The results show that its performance is comparable, or even better in some cases, with widely known FR IQA methods.
Original language | English |
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Title of host publication | 2015 IFIP/IEEE International Symposium on Integrated Network Management, IM 2015 |
Editors | Filip De Turck, Remi Badonnel, Carlos Raniery P. dos Santos, Jin Xiao, Shingo Ata, Voicu Groza |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 1278-1281 |
Number of pages | 4 |
ISBN (Electronic) | 9783901882760 |
DOIs | |
Publication status | Published - 29 Jun 2015 |
Externally published | Yes |
Event | 14th IFIP/IEEE International Symposium on Integrated Network Management, IM 2015: Integrated Management in the Age of Big Data - Shaw Centre, Ottawa, Canada Duration: 11 May 2015 → 15 May 2015 Conference number: 14 http://im2015.ieee-im.org/ |
Publication series
Name | Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management (IM) |
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Publisher | IEEE |
Volume | 2015 |
ISSN (Print) | 1573-0077 |
Conference
Conference | 14th IFIP/IEEE International Symposium on Integrated Network Management, IM 2015 |
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Abbreviated title | IM 2015 |
Country | Canada |
City | Ottawa |
Period | 11/05/15 → 15/05/15 |
Internet address |
Keywords
- Deep learning
- Quality of experience
- Reduced reference image quality assessment
- Restricted Boltzmann machines
- Similarity measure