On-line improvements of the rate-distortion performance in MPEG-2 rate control

Abstract

Existing rate-control research can be summarized into two approaches. One attempts to optimize the rate-distortion (R-D) characteristics of the input source before any decisions about the quantizer step-size assignment are made. As such, rate-control schemes out of this approach incur iterative procedures, high computational cost and encoding delays. The other approach is highlighted by direct buffer-state feedback techniques in predicting the R-D characteristics based on either probabilistic models or on historic information. Both approaches trade suboptimality in the prediction of R-D characteristics for reduced computational cost and delay. In this paper, we combine the simplicity of the predictive models with the high-complexity R-D approaches to design effective rate-control algorithms to exploit the advantages of both approaches: low encoding delay and low complexity, yet optimized estimation of the R-D statistics. Extensive experiments show that improvements over the MPEG-2 scheme with gains of 0.5-1 dB per frame are achieved by the proposed schemes for a variety of test sequences when the same target bit rates are maintained.

Buffer control in H.264/AVC applications by implementing dynamic complexity-rate-distortion analysis

“…As known from the literature, for example from [9], and from our experimental results (Fig. 2), most distortion-complexity-rate (DCR) surfaces are actually exponential distortion-complexity-rate (EDCR) surfaces.…”

A Rate Control Model of MPEG-4 Encoder for Video Transmission over Wireless Sensor Network

“…Improper combination of parameter settings will degrade the video quality. Additionally, there are three categories of approaches in developing the rate control algorithm according to the way for calculating the target bit budget [7]. The first category is buffer-based approaches which compute the target bit budget on a macroblock based on buffer state, the previous bit count or both.…”

Dynamic computational complexity and bit allocation for optimizing H.264/AVC video compression

“…However, the encoding computational complexity in these methods increases with the increase of the length of the video source N. Note that hereinafter, for simplicity, we denote each sequence ffunctionðiÞg N i¼1 , as {function(i)}. As known from the literature, for example from [19], and from our experimental results (Figs. 3-6), most distortion-complexity-rate (DCR) surfaces are actually exponential distortion-complexity-rate (EDCR) surfaces.…”