Psychoacoustics model processing method based on advanced audio decoder

Abstract

The invention discloses a psychoacoustic model processing method based on an advanced audio encoder. The psychoacoustic model processing method includes the following steps: A, the perceptual entropy threshold value and the masking limen of a coding sub-band are obtained by the spectrum energy of the psychoacoustic of the sub-band of the bit stream to be encoded through masked diffusion matrix algorithm; B, anticipated bit consumption of the sub-band is calculated by employing time-frequency correction and anticipated echo correction through the perceptual entropy threshold value and the masking limen of the coding sub-band; C, the psychoacoustic model outputs the anticipated bit consumption of the sub-band, which then serves as a parameter for code rate distortion so as to carry out the encoding process. The psychoacoustic model processing method can obtain the bit consumption of the sub-band through the perceptual entropy more accurately and the anticipated value is taken by the encoder as the parameter for code rate distortion control, thus greatly improving quantizing encoding efficiency and quality of the encoder.

Description

technical field The invention relates to an advanced audio coder, in particular to a processing method based on a psychoacoustic model of the advanced audio coder. Background technique Advanced Audio Coding (AAC) belongs to a kind of transform domain lossy perceptual audio coding. Lossy perceptual audio coding can achieve high compression ratio, but its coding error (quantization noise) is inevitably high. In order to reduce the impact of quantization noise, lossy perceptual audio coding controls the distribution of coding errors by studying the psychoacoustic effects of the human ear, so that the noise generated by quantization errors is difficult to detect. This process is implemented through psychoacoustic models in lossy perceptual coding. The psychoacoustic model controls the distribution of quantization errors by exploiting the auditory masking phenomenon of the human ear. The masking phenomenon is a common psychoacoustic phenomenon, which is determined by the huma...

AI Technical Summary

Problems solved by technology

It can be seen that the sub-band bit consumption prediction number is only obtained by multiplying the normalized perceptual entropy and the number of bits available in the current frame, and the accuracy is not high, which in turn affects the efficiency of rate-distortion control

Moreover, because the traditional psychoacoustic model only considers the simultaneous masking effect of the human ear and ignores the heterochronous masking effect, the encoder cannot use heterochronous masking to improve the encoding quality. Once the pre-masking fails, the quantization noise cannot be masked and pre-echo occurs. The sound quality will be greatly degraded when

Although the AAC standard provides Temporal Noise Shaping (TNS) to weaken the influence of pre-echo, actual tests show that using this module will worsen the sound quality

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