Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC

Abstract To alleviate the computation burden of the depth intra coding in 3D‐HEVC, a complexity reduction scheme based on texture feature and spatio‐temporal correlation is proposed. Firstly, a maximum splitting depth layer decision algorithm is proposed to reduce unnecessary splitting depth layer o...

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Main Authors: Tiansong Li, Li Yu, Hongkui Wang, Yamei Chen
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:IET Image Processing
Online Access:https://doi.org/10.1049/ipr2.12021
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spelling doaj-60fd5f014c87419b94bcdb2c939c2a262021-07-14T13:25:38ZengWileyIET Image Processing1751-96591751-96672021-01-0115120621710.1049/ipr2.12021Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVCTiansong Li0Li Yu1Hongkui Wang2Yamei Chen3The School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan ChinaThe School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan ChinaThe School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan ChinaThe School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan ChinaAbstract To alleviate the computation burden of the depth intra coding in 3D‐HEVC, a complexity reduction scheme based on texture feature and spatio‐temporal correlation is proposed. Firstly, a maximum splitting depth layer decision algorithm is proposed to reduce unnecessary splitting depth layer of the coding tree unit utilising the information of the previous encoded I frame in the same view. Secondly, a new texture complexity model is built by pixel‐based statistical method combined with edge detection. Based on the proposed model, the coding unit block is divided into the smooth block, texture or edge block. On the coding unit level, an early termination of coding unit splitting algorithm for smooth blocks is proposed to filter out unnecessary coding blocks. Thirdly, on the predicting unit level, a fast candidate mode decision algorithm considering predicting unit's types and spatial correlation is proposed to decide the candidate mode list directly. Experimental results describe that the proposed algorithm reduces 53.8% depth intra coding time on average, with 0.43% BD‐rate loss on synthesised views.https://doi.org/10.1049/ipr2.12021
collection DOAJ
language English
format Article
sources DOAJ
author Tiansong Li
Li Yu
Hongkui Wang
Yamei Chen
spellingShingle Tiansong Li
Li Yu
Hongkui Wang
Yamei Chen
Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC
IET Image Processing
author_facet Tiansong Li
Li Yu
Hongkui Wang
Yamei Chen
author_sort Tiansong Li
title Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC
title_short Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC
title_full Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC
title_fullStr Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC
title_full_unstemmed Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC
title_sort fast depth intra coding based on texture feature and spatio‐temporal correlation in 3d‐hevc
publisher Wiley
series IET Image Processing
issn 1751-9659
1751-9667
publishDate 2021-01-01
description Abstract To alleviate the computation burden of the depth intra coding in 3D‐HEVC, a complexity reduction scheme based on texture feature and spatio‐temporal correlation is proposed. Firstly, a maximum splitting depth layer decision algorithm is proposed to reduce unnecessary splitting depth layer of the coding tree unit utilising the information of the previous encoded I frame in the same view. Secondly, a new texture complexity model is built by pixel‐based statistical method combined with edge detection. Based on the proposed model, the coding unit block is divided into the smooth block, texture or edge block. On the coding unit level, an early termination of coding unit splitting algorithm for smooth blocks is proposed to filter out unnecessary coding blocks. Thirdly, on the predicting unit level, a fast candidate mode decision algorithm considering predicting unit's types and spatial correlation is proposed to decide the candidate mode list directly. Experimental results describe that the proposed algorithm reduces 53.8% depth intra coding time on average, with 0.43% BD‐rate loss on synthesised views.
url https://doi.org/10.1049/ipr2.12021
work_keys_str_mv AT tiansongli fastdepthintracodingbasedontexturefeatureandspatiotemporalcorrelationin3dhevc
AT liyu fastdepthintracodingbasedontexturefeatureandspatiotemporalcorrelationin3dhevc
AT hongkuiwang fastdepthintracodingbasedontexturefeatureandspatiotemporalcorrelationin3dhevc
AT yameichen fastdepthintracodingbasedontexturefeatureandspatiotemporalcorrelationin3dhevc
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