Improved Method to Select the Lagrange Multiplier for Rate-Distortion Based Motion Estimation in Video Coding

Abstract

Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Abstract-The motion estimation (ME) process used in the H.264/AVC reference software is based on minimizing a cost function that involves two terms (distortion and rate) that are properly balanced through a Lagrangian parameter, usually denoted as λmotion. In this paper we propose an algorithm to improve the conventional way of estimating λmotion and, consequently, the ME process.First, we show that the conventional estimation of λmotion turns out to be significantly less accurate when ME-compromising events, which make the ME process to perform poorly, happen. Second, with the aim of improving the coding efficiency in these cases, an efficient algorithm is proposed that allows the encoder to choose between three different values of λmotion for the Inter 16x16 partition size. To be more precise, for this partition size, the proposed algorithm allows the encoder to additionally test λmotion = 0 and λmotion arbitrarily large, which corresponds to minimum distortion and minimum rate solutions, respectively. By testing these two extreme values, the algorithm avoids to make large ME errors.The experimental results on video segments exhibiting this type of ME-compromising events reveal an average rate reduction of 2.20% for the same coding quality with respect to the JM15.1 reference software of H.264/AVC. The algorithm has been also tested in comparison with a state-of-the-art algorithm called CALM (Context Adaptive Lagrange Multiplier). Additionally, two illustrative examples of the subjective performance improvement are provided.

Content Adaptive Lagrange Multiplier Selection for Rate-Distortion Optimization in 3-D Wavelet-Based Scalable Video Coding

“…More details on Lagrange optimization technique have been discussed in [ 16 , 20 , 36 ]. This technique is well known in optimization problems where the cost and objective functions are continuous and differentiable.…”

“…As in hybrid video coding-based SVC, rate-distortion optimization (RDO) plays a significant role in SVC in choosing the most suitable coding parameters under communication bandwidth constraints. A critical problem residing in RDO is the selection of the Lagrange multiplier that controls the RD trade-off [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. Sullivan and Wiegand first derived the relationship among the Lagrange multiplier, distortion and bitrate.…”