Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework

Abstract

Abstract-Optimal rate allocation is among the most challenging tasks to perform in the context of predictive video coding, because of the dependencies between frames induced by motion compensation. In this paper, using a recursive rate-distortion model that explicitly takes into account these dependencies, we approach the frame-level rate allocation as a convex optimization problem. This technique is integrated into the recent HEVC encoder, and tested on several standard sequences. Experiments indicate that the proposed rate allocation ensures a better performance (in the rate-distortion sense) than the standard HEVC rate control, and with a little loss w.r.t. an optimal exhaustive research which is largely compensated by a much shorter execution time.

Temporal Adaptive Quantization using Accurate Estimations of Inter and Skip Probabilities

“…Moreover, since Skip consideration should be statistically more efficient at low bitrate, similar results presented in Table II consider only the four highest QP values {27, 32, 37, 42}. We can observe from Table I higher bitrate savings for RDTQ (8) and RDTQ (9) over RDTQ (7) whether the Skip consideration is enabled or not. RDTQ (8) saves in average −1.80% on top of RDTQ (7), while RDTQ (9) has slightly lower performance than RDTQ (8) with −1.58% bitrate reduction.…”

“…The anchor is the x265 encoder without adaptive quantization algorithm. Three Inter probability models, defined in (7), (8) and (9) are compared.…”

“…Recent papers consider dependencies from the Rate-Control (RC) perspective [5], [6], [7]. In [5], Xie et al construct a temporal propagation chain by assuming consistent motion over frames, which allows the estimation of a propagation factor for each Coding Tree Unit (CTU).…”

“…Li et al [6] estimate the distortion propagation frame by frame, using a pre-analysis, in order to provide a consistent video quality over an entire Group of Pictures (GOP). Fiengo et al [7] express the distortion as a convex function of all frames bitrate. Primal-Dual Proximal Algorithm is further used to solve the convex optimization problem and achieve near optimal RC.…”

Optimal Adaptive Quantization Based on Temporal Distortion Propagation Model for HEVC

“…Fiengo et al [18] express distortion as a convex function of all frames bitrate. Primal-Dual Proximal Algorithm is used to solve the convex optimization problem and achieve near optimal Rate-Control (RC).…”