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Calculation of average PSNR differences between RD-curves
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The article was published on 2001-01-01 and is currently open access. It has received 4379 citations till now.read more
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Proceedings ArticleDOI
CNN based post-processing to improve HEVC
TL;DR: This paper adopts a 20-layers CNN (Con-volutional Neural networks) model to extract more meaningful information from the reconstructed error and improve the filtering performance in HEVC.
Journal ArticleDOI
Adaptive Quantization Parameter Cascading in HEVC Hierarchical Coding
TL;DR: This paper formulate the adaptive QPC scheme as a non-linear programming problem and solve it in a scientifically sound way with a manageable low computational overhead to code natural video sequences characterized by diversified textures, motions, and encoder configurations.
Journal ArticleDOI
Rate-Distortion and Complexity Optimized Motion Estimation for H.264 Video Coding
TL;DR: A simple method that determines for each MB which partitions are likely to be optimal, thus reducing the complexity of the ME step and speeds up integer-pel ME by a factor of up to 40 with less than 0.2 dB loss in coding efficiency.
Proceedings ArticleDOI
Deep Learning Based HEVC In-Loop Filtering for Decoder Quality Enhancement
TL;DR: A Convolutional Neural Network (CNN) based architecture for SAO in-loop filtering operation without modifying anything on encoding process is proposed and experimental results show that the proposed model outperformed previous state-of-the-art models in terms of BD-PSNR and BD-BR.
Journal ArticleDOI
Fast Coding Unit Partition Decision for HEVC Using Support Vector Machines
TL;DR: Compared with the state-of-the-art solutions, the proposed fast coding unit (CU) partition decision for use in HEVC encoders based on support vector machine (SVM)-trained offline outperforms the related works in terms of combined rate distortion and complexity.