The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
La prédiction de chromaticité du modèle linéaire à composants croisés (CCLM) est une nouvelle technique introduite dans le codage vidéo polyvalent (VVC), qui utilise la composante de luminance reconstruite pour prédire les parties de chromaticité et peut améliorer les performances de codage. Cependant, cela augmente la complexité du codage. Dans cet article, la manière d'accélérer le processus de prédiction intra-chromatique est étudiée en fonction des caractéristiques de texture. Premièrement, deux observations ont été trouvées grâce aux statistiques expérimentales du processus. L'une est que le choix des modes candidats intra-prédiction de chrominance est étroitement lié à la complexité de la texture de l'unité de codage (CU), et l'autre est que la sélection du mode direct (DM) est étroitement liée à la similarité de texture entre la chromaticité actuelle CU et la luminance correspondante CU. Deuxièmement, un algorithme de décision rapide en mode intra-prédiction de chrominance est proposé sur la base de ces observations. Une métrique modifiée appelée différence de module de somme (SMD) est introduite pour mesurer la complexité de texture de CU et guider le filtrage des modes candidats non pertinents. Pendant ce temps, la mesure de l'indice de similarité structurelle (SSIM) est adoptée pour aider à juger la sélection du mode DM. Les résultats expérimentaux montrent que par rapport au modèle de référence VTM8.0, l'algorithme proposé peut réduire le temps de codage de 12.92 % en moyenne et augmenter le taux BD des composants Y, U et V de seulement 0.05 %, 0.32 %. et 0.29% respectivement.
Zhi LIU
North China University of Technology
Yifan SU
North China University of Technology
Shuzhong YANG
China Academy of Railway Sciences Corporation Limited
Mengmeng ZHANG
North China University of Technology,Beijing Polytechnic College
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copier
Zhi LIU, Yifan SU, Shuzhong YANG, Mengmeng ZHANG, "A Fast Chroma Intra-Prediction Mode Decision Algorithm Based on Texture Characteristics for VVC" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 5, pp. 781-784, May 2021, doi: 10.1587/transinf.2020EDL8140.
Abstract: Cross-component linear model (CCLM) chromaticity prediction is a new technique introduced in Versatile Video Coding (VVC), which utilizes the reconstructed luminance component to predict the chromaticity parts, and can improve the coding performance. However, it increases the coding complexity. In this paper, how to accelerate the chroma intra-prediction process is studied based on texture characteristics. Firstly, two observations have been found through experimental statistics for the process. One is that the choice of the chroma intra-prediction candidate modes is closely related to the texture complexity of the coding unit (CU), and the other is that whether the direct mode (DM) is selected is closely related to the texture similarity between current chromaticity CU and the corresponding luminance CU. Secondly, a fast chroma intra-prediction mode decision algorithm is proposed based on these observations. A modified metric named sum modulus difference (SMD) is introduced to measure the texture complexity of CU and guide the filtering of the irrelevant candidate modes. Meanwhile, the structural similarity index measurement (SSIM) is adopted to help judging the selection of the DM mode. The experimental results show that compared with the reference model VTM8.0, the proposed algorithm can reduce the coding time by 12.92% on average, and increases the BD-rate of Y, U, and V components by only 0.05%, 0.32%, and 0.29% respectively.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020EDL8140/_p
Copier
@ARTICLE{e104-d_5_781,
author={Zhi LIU, Yifan SU, Shuzhong YANG, Mengmeng ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={A Fast Chroma Intra-Prediction Mode Decision Algorithm Based on Texture Characteristics for VVC},
year={2021},
volume={E104-D},
number={5},
pages={781-784},
abstract={Cross-component linear model (CCLM) chromaticity prediction is a new technique introduced in Versatile Video Coding (VVC), which utilizes the reconstructed luminance component to predict the chromaticity parts, and can improve the coding performance. However, it increases the coding complexity. In this paper, how to accelerate the chroma intra-prediction process is studied based on texture characteristics. Firstly, two observations have been found through experimental statistics for the process. One is that the choice of the chroma intra-prediction candidate modes is closely related to the texture complexity of the coding unit (CU), and the other is that whether the direct mode (DM) is selected is closely related to the texture similarity between current chromaticity CU and the corresponding luminance CU. Secondly, a fast chroma intra-prediction mode decision algorithm is proposed based on these observations. A modified metric named sum modulus difference (SMD) is introduced to measure the texture complexity of CU and guide the filtering of the irrelevant candidate modes. Meanwhile, the structural similarity index measurement (SSIM) is adopted to help judging the selection of the DM mode. The experimental results show that compared with the reference model VTM8.0, the proposed algorithm can reduce the coding time by 12.92% on average, and increases the BD-rate of Y, U, and V components by only 0.05%, 0.32%, and 0.29% respectively.},
keywords={},
doi={10.1587/transinf.2020EDL8140},
ISSN={1745-1361},
month={May},}
Copier
TY - JOUR
TI - A Fast Chroma Intra-Prediction Mode Decision Algorithm Based on Texture Characteristics for VVC
T2 - IEICE TRANSACTIONS on Information
SP - 781
EP - 784
AU - Zhi LIU
AU - Yifan SU
AU - Shuzhong YANG
AU - Mengmeng ZHANG
PY - 2021
DO - 10.1587/transinf.2020EDL8140
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2021
AB - Cross-component linear model (CCLM) chromaticity prediction is a new technique introduced in Versatile Video Coding (VVC), which utilizes the reconstructed luminance component to predict the chromaticity parts, and can improve the coding performance. However, it increases the coding complexity. In this paper, how to accelerate the chroma intra-prediction process is studied based on texture characteristics. Firstly, two observations have been found through experimental statistics for the process. One is that the choice of the chroma intra-prediction candidate modes is closely related to the texture complexity of the coding unit (CU), and the other is that whether the direct mode (DM) is selected is closely related to the texture similarity between current chromaticity CU and the corresponding luminance CU. Secondly, a fast chroma intra-prediction mode decision algorithm is proposed based on these observations. A modified metric named sum modulus difference (SMD) is introduced to measure the texture complexity of CU and guide the filtering of the irrelevant candidate modes. Meanwhile, the structural similarity index measurement (SSIM) is adopted to help judging the selection of the DM mode. The experimental results show that compared with the reference model VTM8.0, the proposed algorithm can reduce the coding time by 12.92% on average, and increases the BD-rate of Y, U, and V components by only 0.05%, 0.32%, and 0.29% respectively.
ER -