Two-pass rate control for UHDTV delivery with HEVC

Abstract

Rate control has been regarded as an indispensable video coding tool for virtually any application involving video transmission. With the advent of many flexible tools introduced in the current stateof-the-art High Efficiency Video Coding (HEVC) standard, previous Rate-Distortion (RD) models used for rate control become insufficiently accurate. To overcome this issue, a new RD model has been recently proposed based on a robust correspondence between the rate and Lagrange multiplier λ. However, existing methods based on this model tend to perform sub-optimally after the scene change. In this paper, a two-pass rate control method is proposed, targeting Ultra High Definition Television (UHDTV) applications. In the first pass, a fast encoder with a reduced set of coding tools is used to obtain the data used for rate allocation and model parameter initialisation utilised during the second pass. Multiple encoding steps required to derive this information are avoided with the proposed variable quantisation parameter framework. Experimental evaluation showed that the proposed two-pass rate control method achieves on average 4.4% BD-rate loss, compared with variable bit-rate encoding. That significantly outperforms the state-of-the-art HEVC rate control method with an average BD-rate loss of 8.8%.

JND-aware Two-pass Per-title Encoding Scheme for Adaptive Live Streaming

“…The first-pass uses Constant Bitrate (CBR) encoding to gather encoding statistics, while offline processing is used in the second-pass to detect scene-cuts, precisely allocate target bits, and determine the quantization parameter for each frame. Zupancic et al [26] utilized a fast encoder with a condensed set of coding tools in the first-pass to collect data for rate allocation and model parameter initialization during the second-pass. Wang et al [27] proposed a two-pass VBR control for HEVC, motivated by structural similarity (SSIM), that allocates available bits at the group of pictures (GOP), frame, and coding unit (CU) levels to create a perceptually uniform space.…”

JND-Aware Two-Pass Per-Title Encoding Scheme for Adaptive Live Streaming

“…The first-pass uses CBR encoding to gather encoding statistics, while offline processing is used in the second-pass to detect scene-cuts, precisely allocate target bits, and determine the quantization parameter for each frame. Zupancic et al [29] utilized a fast encoder with a condensed set of coding tools in the first-pass to collect data for rate allocation and model parameter initialization during the second-pass. Wang et al [30] proposed a two-pass VBR control for HEVC, motivated by structural similarity (SSIM), that allocates available bits at the group of pictures (GOP), frame, and coding unit (CU) levels to create a perceptually uniform space.…”

ETPS: Efficient Two-Pass Encoding Scheme for Adaptive Live Streaming

“…Based on the obtained statistics information, such as bitrate, PSNR, and macroblock distributions of each coding type, offline processing is applied to this information to detect scene cuts, accurately allocate target bits, and determine each frame's quantization parameter for the second-pass coding. Zupancic et al [5] used a fast encoder with a reduced set of coding tools as the first-pass, which is used to obtain the data used for rate allocation and model parameter initialization utilized during the second-pass. Wang et al [6] proposed a structural similarity (SSIM) motivated two-pass variable bit rate control algorithm for High Efficiency Video Coding (HEVC) [7].…”