상세정보
학술지
A ParaBoost Stereoscopic Image Quality Assessment (PBSIQA) System
- 저자
- 고현석, Rui Song, C.-C. Jay Kuo
- 발행일
- 201705
- 출처
- Journal of Visual Communication and Image Representation, v.45, pp.156-169
- ISSN
- 1047-3203
- 출판사
- Elsevier
- 협약과제
- 17HR1400, 초고실감 미디어 서비스 실현을 위해 HEVC/3DA 대비 2배 압축을 제공하는 5세대 비디오/오디오 표준 핵심 기술 개발 및 표준화, 김휘용
- 초록
- The problem of stereoscopic image quality assessment, which finds applications in 3D visual content delivery such as 3DTV, is investigated in this work. Specifically, we propose a new ParaBoost (parallel-boosting) stereoscopic image quality assessment (PBSIQA) system. The system consists of two stages. In the first stage, various distortions are classified into a few types, and individual quality scorers targeting at a specific distortion type are developed. These scorers offer complementary performance in face of a database consisting of heterogeneous distortion types. In the second stage, scores from multiple quality scorers are fused to achieve the best overall performance, where the fuser is designed based on the parallel boosting idea borrowed from machine learning. Extensive experimental results are conducted to compare the performance of the proposed PBSIQA system with those of existing stereo image quality assessment (SIQA) metrics. The developed quality metric can serve as an objective function to optimize the performance of a 3D content delivery system.
- KSP 제안 키워드
- 3D content, First stage, Overall performance, Quality Metrics, Quality assessment(IQA), Stereo image quality assessment, Stereoscopic image quality assessment(SIQA), content delivery, delivery system, distortion type, machine Learning