Content based error resilience coding using redundant coding, reference frame modification, and mode decision

Xu, Weiwei; Jiang, Rongxin; Tian, Xiang; Chen, Yaowu

doi:10.1007/s11771-014-2416-3

Cited by 1 publication

(1 citation statement)

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“…However, frequent injection of intra-frames increases the bit rate of the encoded stream. Hence, dynamic and intelligent model-based methods to adjust the intra-frame frequency is heavily investigated in the literature [195], [196]. Duplication of macroblocks inside Efficient rate controlling through intelligent bit allocation, and appropriate coding parameter selection are compelling challenges, specially with the new standards such as VVC, AV1.…”

Section: Error Resilience and Concealment-aware Video Encodingmentioning

confidence: 99%

Measuring, Modeling and Integrating Time-Varying Video Quality in End-to-End Multimedia Service Delivery: A Review and Open Challenges

et al. 2022

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The multimedia delivery chain consists of multiple stages such as content preparation, content delivery via Over-The-Top delivery network and Internet Service Providers network. Within the multimedia service chain, each stage influences the Quality of Experience (QoE) of the end user. The objective of this work is to provide a comprehensive literature survey with future research challenges and opportunities in the field of time-varying video quality in multimedia service delivery. The contribution of this work is two fold: 1) Survey -we provide a review of state-of-the-art works for video quality models to quantify multiple artifacts into a single QoE metric, pooling strategies for global quality measurements, and Continuous Time-Varying Quality (CTVQ) models; 2) Future Challenges and Directions -we investigate ten major research challenges and future directions based on the state-of-the-art for QoE modelling, QoE-aware encoding/decoding and QoE monitoring/management of multimedia streaming in next-generation networks.

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Section: Error Resilience and Concealment-aware Video Encodingmentioning

confidence: 99%