An improved R-D optimized motion estimation method for video coding

Authors:
Alireza Aminlou;Mojtaba Farmani;Mahmoud Reza Hashemi;Omid Fatemi
Affiliations:
Multimedia Processing Laboratory, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran;Multimedia Processing Laboratory, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran;Multimedia Processing Laboratory, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran;Multimedia Processing Laboratory, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
Venue:
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
Year:
2009

Citing 6
Cited 0

An efficient motion estimation technique based on a rate-distortion criterion

ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04
An Estimation-Theoretic Interpretation of Video Rate Distortion Optimization with Lagrangian Formulation

DCC '08 Proceedings of the Data Compression Conference
A video compression scheme with optimal bit allocation among segmentation, motion, and residual error

IEEE Transactions on Image Processing
Rate Distortion Optimization for H.264 Interframe Coding: A General Framework and Algorithms

IEEE Transactions on Image Processing
Rate-distortion optimal motion estimation algorithms for motion-compensated transform video coding

IEEE Transactions on Circuits and Systems for Video Technology
Low-complexity rate-distortion optimal macroblock mode selection and motion estimation for MPEG-like video coders

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

Motion estimation is one of the key tools to achieve a very low bit rate in video coding. The selection of optimum motion vectors (MV) has a significant impact on the quality of the resulted compressed video, in Rate-Distortion (R-D) sense. The established method uses the Lagrange multiplier to optimally select the MV for each block. However, it does not consider the effect of residual coding at the same time with the effect of MVs. In this paper, we have considered the effect of residual coding in motion vector (MV) selection with modeling motion estimation and residual coding as independent processes which results in a new optimization condition. It is based on local optimization, which is the bit allocation between motion estimation and residual coding, and global optimization, which is the bit allocation among different blocks. The proposed motion estimation algorithm results in a PSNR improvement of 0.5- 3.0 dB when it is used in the H.264 standard with block size of 4×4.