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Combined Intra-prediction for High-Efficiency Video Coding

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2011年第7期5卷 1282-1289页

作者： Gabriellini, Andrea Flynn, David Mrak, Marta Davies, Thomas British Broadcasting Corp BBC Res & Dev Dept London W12 7SB England

New activities in the video coding community are focused on the delivery of technologies that will enable economic handling of future visual formats at very high quality. The key characteristic of these new visual systems is the highly efficient compression of such content. In that context this paper presents a novel approach for intra-prediction in video coding based on the combination of spatial closed-and open-loop predictions. This new tool, called Combined Intra-prediction (CIP), enables better prediction of frame pixels which is desirable for efficient video compression. The proposed tool addresses both the rate-distortion performance enhancement as well as low-complexity requirements that are imposed on codecs for targeted high-resolution content. The novel perspective CIP offers is that of exploiting redundancy not only between neighboring blocks but also within a coding block. While the proposed tool enables yet another way to exploit spatial redundancy within video frames, its main strength is being inexpensive and simple for implementation, which is a crucial requirement for video coding of demanding sources. As shown in this paper, the CIP can be flexibly modeled to support various coding settings, providing a gain of up to 4.5% YUV BD-rate for the video sequences in the challenging High-Efficiency Video Coding Test Model.

关键词： High-efficiency video coding intra-prediction open-loop prediction

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PARALLEL PROCESSING FOR COMBINED INTRA prediction IN HIGH EFFICIENCY VIDEO CODING

PARALLEL PROCESSING FOR COMBINED INTRA PREDICTION IN HIGH EF...

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18th IEEE International Conference on Image Processing (ICIP)

作者： Mrak, Marta Gabriellini, Andrea Flynn, David Davies, Thomas British Broadcasting Corp Res & Dev London W12 7SB England

ISBN: (纸本)9781457713033

Advanced intra prediction is one of the key components in highly efficient video coding since it reduces the bit-rate of the most costly intra frames. Combined Intra prediction (CIP) is a novel tool that takes into account well established directional prediction from neighboring blocks, as well as local mean prediction from current block. In this way, it reduces bit-rate by further exploiting spatial redundancy. This paper proposes an implementation that will overcome its potential limitation - limited parallelization capabilities. In order to make it more computationally parallelizable, adaptive open-loop prediction templates have been designed. Experiments have been performed which show that the proposed design preserves coding gains introduced by CIP, while providing a solution for more parallelizable, and therefore faster, implementations.

关键词： video coding intra prediction open-loop prediction parallelization

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Two-layer model predictive control for chemical process model with integrating controlled variables

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CANADIAN JOURNAL OF CHEMICAL ENGINEERING 2020年第1期98卷 237-253页

作者： Yang, Yuanqing Ding, Baocang Xi An Jiao Tong Univ Dept Automat Sch Elect & Informat Engn Xian 710049 Shaanxi Peoples R China

This paper proposes an overall solution to the two-layer model predictive control (MPC) for the integrating controlled variables in the process model. The scheme includes three modules, that is, the open-loop prediction module, the steady-state target calculation (SSTC) module, and the dynamic control module. Based on the real-time output measurements and past inputs, the open-loop prediction module predicts the future outputs in the presence of disturbances. The economic optimization of SSTC is comprised of the feasibility stage and the economics stage, considering constraints of multi-priority ranks. The dynamic control module receives the steady-state targets from SSTC and calculates the control signals. The optimization problems of SSTC and dynamic control operate with the same frequency. This overall method guarantees the consistency of three modules with respect to the model, the constraints, and the targets. The simulation example illustrates that steady-state targets are adjusted dynamically after the occurrence of disturbances, and offset-free control is achieved.

关键词： integrating process model predictive control open-loop prediction steady-state target calculation

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