The DCT coefficients are quantized by appropriately choosing the quantization parameter, and the quantized values are then run-length and Huffman coded.
However, new residuals are calculated by motion compensation, re-quantized by new quantization parameter (QP2), and then re-encoded into the transcoded bitstream.
According to the built linear distortion-quantizer (D-Q) model, before encoding one frame, the quantization parameter can be solved to realize constant quality encoding.
Firstly, the fundamental relationship between perceived coding distortion and quantization parameter (QP) is established.
However, active local motion will produce error distortion and influence the determination of the quantization parameter.
Combining this detector with the equation refines the predicted quantization parameter more precisely.
One critical element in a bit rate control algorithm is the bit production model that predicts the number of produced bits when a certain quantization parameter is used.
Then one perceptual feature in temporal domain is proposed to develop our AQ method, which can generate different quantization parameter (QP) offsets for each coding unit (CU).
The proposed frame-level rate-control method exploits rate-distortion optimization (RDO) to estimate macroblock modes and bitrates for the initial quantization parameter (QP).
Nevertheless, in this paper we show that this model can be refined, especially for static background sequences, so that the coding performance of HEVC can be improved by adaptively modifying the relation between λ and the quantization parameter.
The value of the Lagrangian parameter λ, which balances the weight of the rate and distortion terms, is related to the quantization parameter through a model that has been implemented in the HEVC reference software.
