Results 51 to 60 of about 339 (178)

Fast CU Partition Decision Method Based on Bayes and Improved De-Blocking Filter for H.266/VVC

open access: yesIEEE Access, 2021
The H.266/Versatile Video Coding (VVC) standard is the latest video coding standards released by the Joint Video Exploration Group (JVET). These new technologies have brought more than 40% increase in compression rate and brought huge coding ...
Qiuwen Zhang   +3 more
doaj   +1 more source

Efficient Partition Decision Based on Visual Perception and Machine Learning for H.266/Versatile Video Coding

open access: yesIEEE Access, 2022
H.266/Versatile Video Coding (VVC) is the latest international video coding standard to encode ultra-high-definition video effectively. The quadtree with nested multi-type tree (QT-MTT) structure provides various sizes of coding tree partitioning and ...
Mei-Juan Chen   +6 more
doaj   +1 more source

Fast CU Partition Decision Method Based on Texture Characteristics for H.266/VVC

open access: yesIEEE Access, 2020
The versatile video coding (VVC) is the latest video coding standard, which uses a Multi-Type Tree (MTT) coding structure. Compared with existing video coding standards, this structure can flexibly split coding blocks according to the complex texture ...
Qiuwen Zhang   +4 more
doaj   +1 more source

Low complexity mode selection for H.266/VVC intra coding

open access: yesICT Express, 2022
The newest video compression standard, called Versatile Video Coding (H.266/VVC), outperforms its predecessor High Efficiency Video Coding (HEVC) by up to 50% in the matter of coding performance.
Ei Ei Tun   +2 more
doaj   +1 more source

Sample-Based Gradient Edge and Angular Prediction for VVC Lossless Intra-Coding

open access: yesApplied Sciences
Lossless coding is a compression method in the Versatile Video Coding (VVC) standard, which can compress video without distortion. Lossless coding has great application prospects in fields with high requirements for video quality.
Guojie Chen, Min Lin
doaj   +1 more source

Low Complexity Learning-Based QTMTT Partitioning Scheme for Inter Coding in VVC Encoder

open access: yesIEEE Access
The Versatile Video Coding (VVC) standard, finalized in 2020 by the Joint Video Experts Team (JVET) and the Video Coding Experts Group (VCEG), marks a major advancement in video compression technology, offering a 50% efficiency improvement over its ...
Ibrahim Taabane   +4 more
doaj   +1 more source

Versatile Video Coding-Post Processing Feature Fusion: A Post-Processing Convolutional Neural Network with Progressive Feature Fusion for Efficient Video Enhancement

open access: yesApplied Sciences
Advanced video codecs such as High Efficiency Video Coding/H.265 (HEVC) and Versatile Video Coding/H.266 (VVC) are vital for streaming high-quality online video content, as they compress and transmit data efficiently.
Tanni Das, Xilong Liang, Kiho Choi
doaj   +1 more source

VVC coded distortion prediction model based on frame-level transform coefficient modeling of generalized Gaussian distribution

open access: yesDianxin kexue, 2023
In versatile video coding (VVC), a variety of advanced coding tools work together to achieve excellent coding performance.Compared with high efficient video coding (HEVC), the transform coefficient distribution (TCD) of VVC has sharper peaks.In order to ...
Yiyin GU, Hongkui WANG, Haibin YIN
doaj   +2 more sources

Transform Network Architectures for Deep Learning Based End-to-End Image/Video Coding in Subsampled Color Spaces

open access: yesIEEE Open Journal of Signal Processing, 2021
Most of the existing deep learning based end-to-end image/video coding (DLEC) architectures are designed for non-subsampled RGB color format. However, in order to achieve a superior coding performance, many state-of-the-art block-based compression ...
Hilmi Egilmez   +7 more
doaj   +1 more source

SFNIC: Hybrid Spatial‐Frequency Information for Lightweight Neural Image Compression

open access: yesCAAI Transactions on Intelligence Technology, Volume 10, Issue 6, Page 1717-1730, December 2025.
ABSTRACT Neural image compression (NIC) has shown remarkable rate‐distortion (R‐D) efficiency. However, the considerable computational and spatial complexity of most NIC methods presents deployment challenges on resource‐constrained devices. We introduce a lightweight neural image compression framework designed to efficiently process both local and ...
Youneng Bao   +5 more
wiley   +1 more source

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