A two-level sliding-window VBR controller for real-time hierarchical video coding

Abstract

In this paper, a novel rate control algorithm for real-time VBR hierarchical video coding is proposed. The algorithm works at two levels that are called long-and short-term levels. The long-term level aims at ensuring that the bit count does not exceed the maximum allowed amount for a few-second long window. To this end, it considers a sliding window spanning several GOPs, which is shifted on a GOP basis. In doing so, it avoids the potentially sharp adjustments at the end of the GOP that usually happen in non-sliding approaches. The short-term level aims to provide a proper QP adaptation to fit the target bit budget, which is dictated by the long-term level. It also uses a sliding window, which in this case extends over one GOP. The proposed algorithm has been assessed in realistic conditions for a variety of video sequences. It has been compared to both a constant quality and CBR hierarchical approaches, showing an excellent performance in terms of both rate-distortion and PSNR variation.

A simplified subjective video quality assessment method based on signal detection theory

“…A reference bit rate of 512 kbps was selected for the experiments as well as three different bit rate reductions for each base bit rate. All these operating points were accurately achieved by means of the variable bit rate control algorithm described in [17]. implemented on the Joint Video Team (JVT) H.264 reference software version JM 12.2.…”

In-Layer Multibuffer Framework for Rate-Controlled Scalable Video Coding

“…Likewise, most of the CBR control algorithms proposed for SVC also rely on analytical R-D models for QP estimation; in particular: logarithmic [26], linear [27], quadratic [28], ρ-domain [29], [30], and exponential [31], [32] models have been proposed. Regarding VBR controllers, several solutions for singlelayer coding have been proposed for a variety of applications, such as video streaming and broadcast [33], [34], one-pass digital storage [35], [36], or two-pass digital storage [37], [38]. Other methods, such as those in [39] and [40], take advantage of networking infrastructures supporting VBR transport [12] to improve the visual quality while reducing the buffer delay.…”

“…For SVC, a few approaches have been proposed for video streaming [41], [42], broadcast [43], as well as applications dealing with varying channel conditions [44]. From the R-D modeling point of view, while some of these methods rely on analytical R-D functions for QP estimation [33], [35], [37], [41], [44], others estimate a QP increment with respect to a reference QP value [34], [36], [39], [40], [43], to reduce the QP variation for the sake of visual quality consistency.…”

RBF-Based QP Estimation Model for VBR Control in H.264/SVC

“…Other schemes, such as [21] and [22], have also been proposed taking advantage that VBR video can be easily incorporated in a networking infrastructure that supports VBR transport [2], to improve the visual quality while reducing the buffer delay. From the R-D modeling point of view, instead of using the analytical models described above for real-time CBR applications, several methods have been proposed that relies on the estimation of a QP increment with respect to a reference QP in order to reduce its variation [16], [18], [22].…”

“…With respect to VBR coding, several RC algorithms have been proposed to provide a more consistent visual quality in a variety of applications, such as live streaming and broadcast [15], [16], one-pass digital storage [17], [18], or two-pass digital storage [19], [20]. It should be noted that, for digital storage, the RC algorithm is subject to a budget constraint instead of to a delay constraint.…”