Efficient Quantization Based on Rate–Distortion Optimization for Video Coding

Abstract

Most rate-distortion (R-D) optimized quantization methods of video coding involve an exhaustive search process to determine the optimal quantized transform coefficients of a coding block and are computationally more expensive than the conventional quantization. In this paper, we present a novel analytical method that directly solves the rate–distortion optimization problem in a closed form by employing a rate model for entropy coding. It has the appealing property of low complexity and is easy to implement. The results show that the proposed method is $4\times $ to $40\times $ faster than the previous methods and 3%–5% more efficient in bitrate than the H.264/AVC reference encoder, which uses the conventional quantization, for video coded with the IBBP structure of group of pictures (GOP) in the normal peak signal-to-noise ratio (PSNR) range (30–40 dB).