Frame-Level ρ-Domain R-D Optimization in H.264

Yutao DONG; Xiangzhong FANG; Jing YANG

doi:10.1093/ietisy/e90-d.5.872

Frame-Level ρ-Domain R-D Optimization in H.264

Yutao DONG, Xiangzhong FANG, Jing YANG

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The frame-level R-D optimization in H.264 is very important in video storage scenarios. Among all of the sub-optimal algorithms, a greedy iteration algorithm (GIA) can best lower the computational complexity of frame-level R-D optimization. In order to further lower the computational complexity, a ρ-domain frame-level R-D optimization algorithm is proposed in this letter. Different from GIA, every frame's rate and distortion can be estimated accurately without actual encoding in our proposed algorithm. Simulation results show that our proposed algorithm can lower the computational complexity greatly with negligible variation in peak signal-to-noise ratio (PSNR) compared with GIA.

Publication: IEICE TRANSACTIONS on Information Vol.E90-D No.5 pp.872-876

Publication Date: 2007/05/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1093/ietisy/e90-d.5.872

Type of Manuscript: LETTER

Category: Image Processing and Video Processing

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Yutao DONG, Xiangzhong FANG, Jing YANG, "Frame-Level ρ-Domain R-D Optimization in H.264" in IEICE TRANSACTIONS on Information, vol. E90-D, no. 5, pp. 872-876, May 2007, doi: 10.1093/ietisy/e90-d.5.872.
Abstract: The frame-level R-D optimization in H.264 is very important in video storage scenarios. Among all of the sub-optimal algorithms, a greedy iteration algorithm (GIA) can best lower the computational complexity of frame-level R-D optimization. In order to further lower the computational complexity, a ρ-domain frame-level R-D optimization algorithm is proposed in this letter. Different from GIA, every frame's rate and distortion can be estimated accurately without actual encoding in our proposed algorithm. Simulation results show that our proposed algorithm can lower the computational complexity greatly with negligible variation in peak signal-to-noise ratio (PSNR) compared with GIA.
URL: https://globals.ieice.org/en_transactions/information/10.1093/ietisy/e90-d.5.872/_p

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@ARTICLE{e90-d_5_872,
author={Yutao DONG, Xiangzhong FANG, Jing YANG, },
journal={IEICE TRANSACTIONS on Information},
title={Frame-Level ρ-Domain R-D Optimization in H.264},
year={2007},
volume={E90-D},
number={5},
pages={872-876},
abstract={The frame-level R-D optimization in H.264 is very important in video storage scenarios. Among all of the sub-optimal algorithms, a greedy iteration algorithm (GIA) can best lower the computational complexity of frame-level R-D optimization. In order to further lower the computational complexity, a ρ-domain frame-level R-D optimization algorithm is proposed in this letter. Different from GIA, every frame's rate and distortion can be estimated accurately without actual encoding in our proposed algorithm. Simulation results show that our proposed algorithm can lower the computational complexity greatly with negligible variation in peak signal-to-noise ratio (PSNR) compared with GIA.},
keywords={},
doi={10.1093/ietisy/e90-d.5.872},
ISSN={1745-1361},
month={May},}

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TY - JOUR
TI - Frame-Level ρ-Domain R-D Optimization in H.264
T2 - IEICE TRANSACTIONS on Information
SP - 872
EP - 876
AU - Yutao DONG
AU - Xiangzhong FANG
AU - Jing YANG
PY - 2007
DO - 10.1093/ietisy/e90-d.5.872
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E90-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2007
AB - The frame-level R-D optimization in H.264 is very important in video storage scenarios. Among all of the sub-optimal algorithms, a greedy iteration algorithm (GIA) can best lower the computational complexity of frame-level R-D optimization. In order to further lower the computational complexity, a ρ-domain frame-level R-D optimization algorithm is proposed in this letter. Different from GIA, every frame's rate and distortion can be estimated accurately without actual encoding in our proposed algorithm. Simulation results show that our proposed algorithm can lower the computational complexity greatly with negligible variation in peak signal-to-noise ratio (PSNR) compared with GIA.
ER -