메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Thuc Nguyen Huu (VNU-University of Engineering and Technology) Duong Dinh Trieu (VNU-University of Engineering and Technology) Byeungwoo Jeon (Sungkyunkwan University) Xiem HoangVan (VNU-University of Engineering and Technology)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.6 No.6
발행연도
2017.12
수록면
428 - 436 (9page)
DOI
10.5573/IEIESPC.2017.6.6.428

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
Scalable High Efficiency Video Coding (SHVC) has been emerging as an efficient video coding solution for adaptive video streaming and conferencing. SHVC is designed with a layered coding structure in which High Efficiency Video Coding (HEVC) tools are employed as core elements. However, compression efficiency and error sensitivity associated with efficient HEVC tools make this scalable codec less attractive for practical video transmission, especially when the loss of packets or video frames occurs. This problem severely impacts the display quality of received video. To address this problem, we propose efficient error concealment (EC) methods that compensate for a whole frame that is lost and that mitigate the error propagation problem occurring in practical video transmissions using SHVC. The presented EC methods mainly rely on the decoded information; thus, it is easily integrated into the SHVC decoder as a post-processing component. The experimental results obtained for both subjective and objective quality assessments show that the inter-layer correlation-based EC approach typically provides the highest concealed frame quality; thus, it is highly recommended for practical video transmission.

목차

Abstract
1. Introduction
2. Related Work
3. Proposed EC Solutions
4. Performance Evaluation
5. Conclusion
References

참고문헌 (20)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2018-569-001667046