A New Rate Control Scheme For Video Coding Based On Region Of Interest

A Frame-Level Constant Bit-Rate Control Using Recursive Bayesian Estimation for Versatile Video Coding

“…Several schemes for an R-Q mixture model were developed by exploiting the different characteristics of pdfs in various CU depth levels [8][9][10][11]. The R-Q mixture model is expressed as a multiple mixture model of Laplacian function:…”

“…where x represents TC values, pi is the portion of pixels in the i-th CU depth per frame, NCU is the total number of CU depth levels (= 4 for HEVC), i φ is the Laplacian model parameter as 2 i σ , where σi is the standard deviation of TC values in the i-th CU depth per frame, and ℜ is the set of real numbers. It is demonstrated that multiple R-Q models can be better fitted to the pdfs of actual TC values [8][9][10][11]. Gao et al proposed a synthesized pdf model by minimizing the Kullback-Leibler divergence, and then the synthesized pdf model is collaborated with the R-ρ model to increase the R-D estimation accuracy [35].…”

“…An R-Q (rate-quantization) model such as the Laplacian mixture model (LMM) [8][9][10][11] has increased the rate estimation performance in HEVC [6]. However, our previous work [12] demonstrated that the LMM is less effective for R-D estimation when applied for VVC Test Model (VTM-5.0) [1] compared to the HM [13].…”

Acceleration for HEVC Encoder by Bimodal Segmentation of Rate-Distortion Cost and Accurate Determination of Early Termination and Early Split

“…A hierarchical complexity control approach in [10] accurately reduces the coding complexity to the target bandwidth and keeps video quality simultaneously. Reference [11] proposes a rate control scheme for region of interest (ROI) based on Fourier transform and neuron network. Reference [12] proposes an early SKIP mode decision, utilizing the characteristics of the SKIP mode to reduce the complexity.…”

“…In a summary, in this sub-section, we apply a one-sided Chebyshev's inequality to obtain the threshold for early termination (Th ET ) and the threshold for early split (Th ES ) as shown in (11) and (12). According to the statistical data, the 2-D hyperplanes are fitted by considering QP variations and CU sizes for acquiring proper parameters (k s and k ns ) of Th ES and Th ET , respectively.…”