H.264/SVC Mode Decision Based on Mode Correlation and Desired Mode List
September 22, 2020 ยท Declared Dead ยท ๐ International Journal of Automation and Computing
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
L. Balaji, K. K. Thyagharajan
arXiv ID
2009.10708
Category
cs.MM: Multimedia
Citations
12
Venue
International Journal of Automation and Computing
Last Checked
2 months ago
Abstract
The design of video encoders involves the implementation of fast mode decision (FMD) algorithm to reduce computation complexity while maintaining the performance of the coding. Although H.264/scalable video coding (SVC) achieves high scalability and coding efficiency, it also has high complexity in implementing its exhaustive computation. In this paper, a novel algorithm is proposed to reduce the redundant candidate modes by making use of the correlation among layers. The desired mode list is created based on the probability to be the best mode for each block in the base layer and a candidate mode selection in the enhancement layer by the correlations of modes among the reference frame and current frame. Our algorithm is implemented in joint scalable video model (JSVM) 9.19.15 reference software and the performance is evaluated based on the average encoding time, peak signal to noise ratio (PSNR) and bit rate. The experimental results show 41.89% improvement in encoding time with minimal loss of 0.02dB in PSNR and 0.05% increase in bit rate.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Multimedia
R.I.P.
๐ป
Ghosted
๐
๐
Old Age
Quality Assessment of In-the-Wild Videos
R.I.P.
๐ป
Ghosted
Viewport-Adaptive Navigable 360-Degree Video Delivery
R.I.P.
๐ป
Ghosted
A Comprehensive Survey on Cross-modal Retrieval
R.I.P.
๐ป
Ghosted
An Overview of Cross-media Retrieval: Concepts, Methodologies, Benchmarks and Challenges
R.I.P.
๐ป
Ghosted
A Convolutional Neural Network Approach for Post-Processing in HEVC Intra Coding
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted