ABSTRACT
In the first part of this paper, we derive a source model describing the relationship between the rate, distortion, and quantization steps of the dead-zone plus uniform threshold scalar quantizers with nearly uniform reconstruction quantizers for generalized Gaussian distribution. This source model consists of rate-quantization, distortion-quantization (D-Q), and distortion-rate (D-R) models. In this part, we first rigorously confirm the accuracy of the proposed source model by comparing the calculated results with the coding data of JM 16.0. Efficient parameter estimation strategies are then developed to better employ this source model in our two-pass rate control method for H.264 variable bit rate coding. Based on our D-Q and D-R models, the proposed method is of high stability, low complexity and is easy to implement. Extensive experiments demonstrate that the proposed method achieves: 1) average peak signal-to-noise ratio variance of only 0.0658 dB, compared to 1.8758 dB of JM 16.0's method, with an average rate control error of 1.95% and 2) significant improvement in smoothing the video quality compared with the latest two-pass rate control method.
ABSTRACT
This paper provides a systematic rate-distortion (R-D) analysis of the dead-zone plus uniform threshold scalar quantization (DZ+UTSQ) with nearly uniform reconstruction quantization (NURQ) for generalized Gaussian distribution (GGD), which consists of two aspects: R-D performance analysis and R-D modeling. In R-D performance analysis, we first derive the preliminary constraint of optimum entropy-constrained DZ+UTSQ/NURQ for GGD, under which the property of the GGD distortion-rate (D-R) function is elucidated. Then for the GGD source of actual transform coefficients, the refined constraint and precise conditions of optimum DZ+UTSQ/NURQ are rigorously deduced in the real coding bit rate range, and efficient DZ+UTSQ/NURQ design criteria are proposed to reasonably simplify the utilization of effective quantizers in practice. In R-D modeling, inspired by R-D performance analysis, the D-R function is first developed, followed by the novel rate-quantization (R-Q) and distortion-quantization (D-Q) models derived using analytical and heuristic methods. The D-R, R-Q, and D-Q models form the source model describing the relationship between the rate, distortion, and quantization steps. One application of the proposed source model is the effective two-pass VBR coding algorithm design on an encoder of H.264/AVC reference software, which achieves constant video quality and desirable rate control accuracy.
