Iterative rate-distortion optimization of H.264 with constant bit rate constraint.
In this paper, we apply the primal-dual decomposition and subgradient projection methods to solve the rate-distortion optimization problem with the constant bit rate constraint. The primal decomposition method enables spatial or temporal prediction dependency within a group of picture (GOP) to be processed in the master primal problem. As a result, we can apply the dual decomposition to minimize independently the Lagrangian cost of all the MBs using the reference software model of H.264. Furthermore, the optimal Lagrange multiplier lambda* is iteratively derived from the solution of the dual problem. As an example, we derive the optimal bit allocation condition with the consideration of temporal prediction dependency among the pictures. Experimental results show that the proposed method achieves better performance than the reference software model of H.264 with rate control.
An
Cheolhong
C
Electrical and Computer Engineering Department, University of California, San Diego, La Jolla, CA 92093, USA. chan@ucsd.edu
Nguyen
Truong Q
TQ
D000465:Algorithms; D016477:Artifacts; D044962:Data Compression / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D014741:Video Recording / Q000379:methods*