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Journal Article
Enhanced Pruning Algorithm for Improving Visual Quality in MPEG Immersive Video
- Authors
- Hong-Chang Shin, Jun-Young Jeong, Gwangsoon Lee, Muhammad Umer Kakli, Junyoung Yun, Jeongil Seo
- Issue Date
- 2022-02
- Citation
- ETRI Journal, v.44, no.1, pp.73-84
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원 (ETRI)
- Language
- English
- Type
- Journal Article
- Abstract
- The moving picture experts group (MPEG) immersive video (MIV) technology has been actively developed and standardized to efficiently deliver immersive video to viewers in order for them to experience immersion and realism in various realistic and virtual environments. Such services are provided by MIV technology, which uses multiview videos as input. The pruning process, which is an important component of MIV technology, reduces interview redundancy in multiviews videos. The primary aim of the pruning process is to reduce the amount of data that available video codec must handle. In this study, two approaches are presented to improve the existing pruning algorithm. The first method determines the order in which images are pruned. The amount of overlapping region between the source views is then used to determine the pruning order. The second method considers global region-wise color similarity to minimize matching ambiguity when determining the pruning area. The proposed methods are evaluated under common test condition of MIV, and the results show that incorporating the proposed methods can improve both objective and subjective quality.
- KSP Keywords
- Color Similarity, Immersive video, Moving picture experts group(MPEG), Multiview video, Pruning algorithm, Subjective quality, Test condition, Video codec, Virtual environment, Visual quality, first method
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
