Quantized voice-frequency coding method based on minimized global noise masking ratio criterion and entropy coding

Abstract

The present invention relates to a voice frequency coding method containing two portions of coding voice signal and quantization, and includes the following steps: dividing time domain voice frequency signal, into the framke with a certain length; making time domain signal of every frame undergo the process of time frequency conversion to obtain frequency domain coefficient, dividing the frequency domain coefficient of every frame into different frequency subbands, at the same time, making the time domain signal undergo the process of psychological acoustic model analysis to obtain noise masking threshold of every frequency domain subband, under the control of the noise masking threshold of every subband distributing making bit distribution and quantization of frequency domain coefficient of every subband, and making entropy coding so as to effectively raise compression efficiency.

Description

technical field [0001] The invention relates to a processing method for encoding and quantizing an input audio signal, in particular to an audio encoding method based on minimizing the global noise-masking ratio criterion and entropy encoding and quantization. technical background [0002] The LAYER1 (MP1) and LAYER2 (MP2) standards for audio coding in the MPEG1 standard are two audio-perceptual coding standards. In these two standards, the input time-domain audio signal is divided into blocks of frame length; each frame The time domain signal is transformed into frequency domain coefficients, and the frequency domain coefficients are divided into several frequency domain subbands; at the same time, the psychoacoustic model analyzes the time domain signal of the current frame to obtain the noise masking threshold of each frequency domain subband; then bit allocation The process progressively allocates the number of available bits to each subband such that the largest noise-m...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of the above two quantization methods, the quantization method proposed by the present invention can quickly achieve the optimal perceptual quantization result, which not only overcomes the shortcomings of low quantization accuracy of MP1 and MP2, but also overcomes the disadvantage of high AAC computational complexity. Moreover, in the case of insufficient number of available bits, the quantization can also achieve the most perceptually optimal solution.

Images