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Towards Prediction Optimality in Vid...

Li, Shunyao.

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Towards Prediction Optimality in Video Compression and Networking.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Towards Prediction Optimality in Video Compression and Networking./
作者:	Li, Shunyao.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	104 p.
附註:	Source: Dissertations Abstracts International, Volume: 79-11, Section: B.
Contained By:	Dissertations Abstracts International79-11B.
標題:	Computer Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10748712
ISBN:	9780355876512

Towards Prediction Optimality in Video Compression and Networking.
Li, Shunyao.

Towards Prediction Optimality in Video Compression and Networking. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 104 p.

Source: Dissertations Abstracts International, Volume: 79-11, Section: B.

Thesis (Ph.D.)--University of California, Santa Barbara, 2018.

This item is not available from ProQuest Dissertations & Theses.

In modern video compression and communication systems, prediction is one of the key schemes to exploit spatial and temporal redundancies. However, current approaches are suboptimal as they do not fully exploit the spatial and temporal correlations within signals. This dissertation focuses on the optimal prediction algorithms that fully utilize the correlations, and the optimal design of predictors that accounts for the rich variety of video statistics as well as the instability due to quantization error propagation in the closed-loop video coding system. Complementary to predictive coding, we also expand the design framework to the general predictive coding system, focusing on the optimal transform design that spatially de-correlates the residual data, leading to better compactness and compression performance. The contributions in this dissertation cover the topics of spatial (intra) prediction, temporal (inter) prediction, the layered prediction in scalable coding and transform design. The contributions have been proposed to or accepted in multiple video coding standardization efforts including the Moving Picture Experts Group (MPEG) and the Alliance for Open Media (AOM), and have provided significant improvements in the video compression performance.

ISBN: 9780355876512Subjects--Topical Terms:

1567821
Computer Engineering.
Subjects--Index Terms:

Optimization

Towards Prediction Optimality in Video Compression and Networking.
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520 $a In modern video compression and communication systems, prediction is one of the key schemes to exploit spatial and temporal redundancies. However, current approaches are suboptimal as they do not fully exploit the spatial and temporal correlations within signals. This dissertation focuses on the optimal prediction algorithms that fully utilize the correlations, and the optimal design of predictors that accounts for the rich variety of video statistics as well as the instability due to quantization error propagation in the closed-loop video coding system. Complementary to predictive coding, we also expand the design framework to the general predictive coding system, focusing on the optimal transform design that spatially de-correlates the residual data, leading to better compactness and compression performance. The contributions in this dissertation cover the topics of spatial (intra) prediction, temporal (inter) prediction, the layered prediction in scalable coding and transform design. The contributions have been proposed to or accepted in multiple video coding standardization efforts including the Moving Picture Experts Group (MPEG) and the Alliance for Open Media (AOM), and have provided significant improvements in the video compression performance.
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653 $a Transform
653 $a Video compression
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