Cost-Effective Frame-Layer H.264 Rate Control for Low Bit Rate Video

Abstract

The rate control is important to allocate bits efficiently for getting better performance, such as high quality, low fluctuation of quality and low mismatch between a target bit rate and an encoded bit rate. In this paper, we present an improved frame-layer H.264/AVC rate control scheme using enhanced complexity measure, scene-change detection, and quantization parameter adjustment for low bit rate video. Especially, our complexity measure contains not only the residual information but also the motion information. We use the motion vector difference encoded previously as motion information for low computation-load encoder. Experimental results show that Y-PSNR and bit-rate mismatch are remarkably improved and the fluctuation of Y-PSNR is similar as compared with the conventional H.264/AVC rate control scheme (JVT-G012).

FMO-based H.264 frame layer rate control for low bit rate video transmission

“…In this article, we take a more proactive approach by proposing enhancements to the H.264/AVC frame layer rate control regardless of the FMO mapping, using an explicit FMO map type, to better control the rate when FMO is enabled. The approach taken is similar to other studies on rate control [6][7][8] where frame complexity, target bits and QP adjustment schemes are made to enhance the frame layer rate control. We take this approach further by considering the number of motion vector differences to enhance the MAD and develop a new header bits model with FMO enabled, using a different number of slice groups.…”

“…Then, the frame complexity (FC i ) measure for the ith frame is computed by combining the MAD ratio and the N nzMVD ratio, as shown in (6). The model parameter b is set empirically with a value of 0.3 for complex sequences and 0.7 for simple sequences by comparing the variance of the sum of N nzMVDratio per frame with a threshold.…”

“…In [5], gradientbased complexity measures used in still images are adopted as a measure of frame complexity. The use of the MAD ratio and peak signal-to-noise ratio (PSNR)-based complexity measure has also been explored [6][7][8] to adjust QP and the bit allocation. In [9], a rate control technique for offline processing using a video quality metric and evolution strategy was proposed; however, this scheme is still computationally complex.…”

Towards a Stringent Bit-Rate Conformance for Frame-Layer Rate Control in H.264/AVC

“…This approach is ideal for the transmission of stored videos like video-on-demand, but is normally not suitable for applications such videoconferencing. Other approaches made use of complexity measures that are predicted [8,10] or by using some image processing techniques [4,6] or histogram difference techniques [7]. All these approaches have shown that scene change can be detected reasonably well, however, none of them account for the differences between I-frames, P-frames and B-frames in their complexity measures.…”