Prediction architecture based on block matching statistics for mixed spatial-resolution multi-view video coding
- Submitting institution
-
University of East London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 27
- Type
- D - Journal article
- DOI
-
10.1186/s13640-017-0164-7
- Title of journal
- EURASIP Journal on Image and Video Processing
- Article number
- 15
- First page
- -
- Volume
- 2017
- Issue
- 1
- ISSN
- 1687-5281
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
1 - Intelligent Systems
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The aim of this work was to address deficiencies of prediction architectures of mixed spatial resolution multi-view video coding using state-of-the-art H.264/AVC. Significant improvement in bit rate reduction, coding time and memory consumption is achieved. The major key step was to derive, select, order and adapt reference frames combined with suitable decimation and interpolation methods. Results were substantiated using a comprehensive set of standardised datasets tested under extreme conditions. This included scenarios with hard scene changes.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -