Multi-Objective Optimization and Characterization of Pareto Points for Scalable Coding

In this paper, we formulated the optimal bit-allocation problem for a scalable codec for images/videos as a graph-based constrained vector-valued optimization problem with many optimal solutions, which are referred to as Pareto points. Pareto points are generally derived using weighted sum scalariza...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems for video technology Vol. 29; no. 7; pp. 2096 - 2111
Main Authors: Hwang, Wen-Liang, Lee, Chia-Chen, Peng, Guan-Ju
Format: Journal Article
Language:English
Published: New York IEEE 01.07.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Codec
Codecs
Coding
Distortion
Encoding
multi-criterion optimization
Multiple objective analysis
Optimization
Pareto optimization
Rate-distortion
Resource management
Scalability
Scalable coding
Theorems
Video compression
ISSN:1051-8215, 1558-2205
Online Access:Get full text
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Summary:In this paper, we formulated the optimal bit-allocation problem for a scalable codec for images/videos as a graph-based constrained vector-valued optimization problem with many optimal solutions, which are referred to as Pareto points. Pareto points are generally derived using weighted sum scalarization; however, it has yet to be determined whether all Pareto points can be derived using this approach. This paper addresses this issue. When presented as a theorem, our results indicate that as long as the rate-distortion function of each resolution is strictly decreasing and convex and the Pareto points form a continuous curve, then all Pareto points can be derived using scalarization. The theorem is verified using the state-of-the-art scalable coding method H.264/SVC and a scalability extension of High Efficiency Video Coding (HEVC). We highlight a number of easily interpretable Pareto points that represent a good trade-off between candidate resolutions. The proximity point is defined as the Pareto point closest to the ideal performance for each resolution. We also model the Pareto points as a function of total bit rate and demonstrate that the Pareto points at other target bit rates can be predicted.
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ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2018.2851999