CN1154084C - Audio coding/decoding technology based on pseudo wavelet filtering - Google Patents
Audio coding/decoding technology based on pseudo wavelet filtering Download PDFInfo
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Abstract
The present invention relates to an audio signal compression technique which is a branch which develops quickly in the filed of modern information processing. The present invention is characterized in that audio signals are decomposed into frames whose length is L, and an obtained frame sequence is loaded into a signal type judgement unit; the current frame sequence is parallelly loaded into a psychological acoustic analysis unit and a pseudo wavelet filtering unit of signals of a corresponding type; a pseudo wavelet coefficient is organized according to a subband in sequence, and the pseudo wavelet coefficient is divided into scale factor bands according to time frequency characteristics of the pseudo wavelet coefficient; the reorganized pseudo wavelet coefficient is processed in a companding mode, and then the processed pseudo wavelet coefficient is loaded into a quantization unit which has minimum global perception distortion; a quantization result is input into a self-adaptive Huffman encoder for entropy encoding to form an audio compression code stream. A pseudo wavelet filtering device can achieve the switch between quick-change signal filtering and slow-change signal filtering in real time and achieves the seamless connection of filtering from slow-change signals to quick-change signals with filtering from the quick-change signals to the slow-change signals.
Description
Technical field
The present invention relates to the compress technique of the branch-sound signal of a fast development in the present information process field.
Background technology
We know by the source coding technique principle, some linear transformations or sub-band filter can cause approaching zero high frequency coefficient, in other words, the most information that time-domain signal comprises can be converted or focus on a son of frequency domain or time-frequency domain coefficient and concentrate, so the audio signal compression technology adopts conversion or sub-band filter as the means that improve code efficiency widely.
Present most of encode/decode audio signal scheme all adopts Modulated Discrete CosineTransform (MDCT) as its bank of filters, MDCT proposed (" Subband/Transform Coding Using Filter BankDesigns Based on Time Domain Aliasing Cancellation " by Princen and Bradley in 1987, Proceedings of theICASSP 1987, pp 2161-2164), it becomes isometric subband to a signal decomposition with overlapping block with dynamic window, because the speciality of cosine series function and the quantizing noise in the encoding-decoding process, the use meeting of coefficient reconstruct and reverse MDCT forms ripple around the hop signal that synthesizes.Human auditory system's backward masking timeliness is longer than the forward masking timeliness, the rear end of PCM (pulse-code modulation) frame is in the backward masking timeliness usually, therefore, ripple after the prominent exceeding signal can not be heard, if the forward masking timeliness can not cover the front end of PCM frame, the ripple of prominent exceeding signal front can form appreciable noise, and this noise is called as Pre echoes.
For suppressing or eliminating this pre-echo, less MDCT block length should be used so that the ripple of prominent exceeding signal front is limited in the forward masking timeliness, because block length is directly proportional with code efficiency, a kind of algorithm of selecting the MDCT block length automatically and accurately can be eliminated or suppress pre-echo and optimize the distortion performance of codec.In the past few years, some are used to suppress or the length selection method of eliminating pre-echo is suggested and is used in different systems, and for example Sony Corporation's peak value of being used for ATRAC coding techniques continuous subframes is distinguished the perception entropy judgement strategy of strategy and MPEG AAC etc.These two kinds of strategies all have the limitation of himself, see also " a kind of length selection method based on adaptive threshold and typical sample prediction " in detail, application number: 01134556.x.
As mentioned above, when using the audio coder of piece conversion, input signal is of short duration on the time domain and significant variation (hop signal) can cause the pre-echo noise when the forward masking timeliness can not cover the front end of PCM frame; In order to suppress or to eliminate this pre-echo, short piece should be used so that the ripple of hop signal front is limited in the forward masking timeliness, yet, thereby less block length causes the decline of frequency domain resolution to reduce code efficiency inevitably, to having the input term signal of hop, between code efficiency and pre-echo elimination, there is an equilibrium problem.
Lot of experiments to human auditory characteristics shows, human auditory system can mark off the combinations of bands of a non-equiband by frequency distribution, people's ear has tangible difference to the sensitivity of sound in each frequency band range, and these frequency band ranges are called critical subband (criticalsubband).MDCT is as a defective of the bank of filters of equiband: can not utilize the auditory properties of people's ear to realize the removal to greatest extent of redundant information fully, promptly realize the undistorted coding under the high compression ratio more.Utilize the time-frequency localization and the multiresolution analysis character of small echo and wavelet package transforms, structure based on the non-wide sub-filter of human auditory's feature to replace the equiband sub-filter in the existing algorithm.After the sub-band division of more being pressed close to critical subband, can utilize psychoacoustic model to compress better, for guaranteeing that further improving ratio of compression under the transparent situation of reconstruct tonequality provides possibility.But the wave filter cascade characteristic of wavelet transformation makes the frequency selectivity of wavelet filter group can not can very high, has limited the efficient based on the audio coding scheme of wavelet transformation.
Content of the present invention
The objective of the invention is to: (1) is in calculating that makes full use of the piece conversion and code efficiency, utilize the multiresolution performance of pseudo wavelet filtering device, coding audio signal is more pressed close to the frequency band division of human auditory's feature, thereby effectively improve code efficiency; (2) adopt signal type recognition techniques efficiently, improve the precision of distinguishing of signal type, and improve the counting yield of psychoacoustic model simultaneously; (3) adopt more sane quantification optimisation strategy, improve and quantize quality and optimal speed; (4) adopt the noise shaping technology of more optimizing, when effectively reducing the dynamic range of signal, make quantizing noise be more conducive to perceptual mask.
The technical scheme of the present invention for realizing that goal of the invention proposed
Pseudo-small echo audio coding/decoding device has adopted the pseudo wavelet filtering device of excellent performance, and has designed the quantizer and the entropy coder of suitable pseudo wavelet filtering device.The core feature of its scrambler is:
A) sound signal resolves into the frame that length is L, and does delay and handle;
B) the top frame sequence that obtains is sent into the signal type judging unit, analyze the current demand signal type, change severe degree according to it and be divided into tempolabile signal and fast changed signal;
C) according to b) the result, with parallel psychoacoustic analysis unit and the pseudo wavelet filtering unit of sending into the corresponding types signal of present frame sequence, calculate the auditory masking amount and calculate the pseudo wavelet filtering coefficient;
D) pseudo-wavelet coefficient is organized by the subband order, and be divided into the scale factor band by its time-frequency characteristic;
E) the pseudo-wavelet coefficient after the re-organized is done companding and handle, the companding function is as follows
Wherein l is a positive integer, and α is the real number less than 1;
F) the pseudo-wavelet coefficient after companding is handled is sent into the quantifying unit of overall perceptual distortion minimum, the corresponding linear quantizer of each scale factor band, and quantitative formula is:
q(x)＝x′·2
β·scale_fac， (2)
L wherein, α is with (1) formula, and β is the real number less than 1, and scale factor scale_fac is a positive integer.
Quantizing process is for comprising a quantization loop, each circulation is to select current masking by noise than maximum scale factor band, give this subband minimum possible bit number distributing to additional allocation on the bit number basis of this subband originally then, and upgrade the masking by noise ratio of this subband; So circulation surpasses target bits until required bit.
G) with the Huffman scrambler of quantized result (scale factor and quantization parameter) input adaptive, scrambler is selected the Huffman code table according to the statistical property of present frame sequence, carries out entropy coding, forms the audio compression code stream.
The core feature of its demoder is:
A), solve the scale factor of present frame and the model type of quantization parameter and present frame with compressed bit stream input adaptive Huffman demoder.
B) with scale factor and quantization parameter input inverse DCT, calculate the pseudo-wavelet coefficient of inverse quantization, the formula of inverse quantization is
Wherein l, α, the same formula of β meaning (1), (2), q (x) and iq (x) are respectively quantization parameter and dequantized coefficients.
C) current frame signal type and the dequantized coefficients that just obtained are imported pseudo-small echo liftering unit, calculate the reconstruct time domain sequences.
D) the reconstruct time domain sequences that obtains is carried out delay compensation, calculate reconstruct time-domain audio sequence.
Pseudo wavelet filtering device time-frequency selectivity characteristic
Desired pseudo-wavelet filter has such characteristic in the technical scheme, it is a kind of non-equiband bank of filters technology that the multiresolution analysis performance of similar small echo is arranged, both success had overcome wavelet transformation counting yield and the not high weakness of frequency selective power, have the excellent properties that similar wavelet multiresolution rate is analyzed simultaneously, make to keep high code efficiency steady-state signal and transient signal.
Following experiment can clearly illustrate the excellent properties of pseudo wavelet filtering device.
Get shock response length and only be four pseudo wavelet filtering devices of 64, calculate their frequency response.Then, we utilize four wavelet filters of Daubechies orthogonal wavelet basis function and the corresponding frequency band range of wavelet packet technical construction, and the shock response length of wherein the longest wavelet filter is 1000, and calculates the frequency response of four wavelet filters.
Can be clearly seen that, response length only is that the secondary lobe of the amplitude response of 64 pseudo wavelet filtering device is about low 9 dB of secondary lobe of amplitude response of 1000 wavelet filter than response length, that is to say, the frequency selectivity of pseudo wavelet filtering device is higher than wavelet filter, also it be easy to show that this conclusion by calculation code gain.According to the auditory properties of people's ear, this characteristic of pseudo-small echo helps the raising of audio coding performance.
The pseudo wavelet filtering device is handled the dirigibility of fast changed signal and tempolabile signal
Compare with the AAC standard among the mpeg, the pseudo wavelet filtering device also has such advantage, can realize the switching of fast changed signal filtering and tempolabile signal filtering in real time, specifically, the pseudo wavelet filtering device does not need the length frame in the AAC standard and the transition block of short long frame, but realized to the filtering of tempolabile signal to the filtering of fast changed signal and to the filtering of fast changed signal to seamless link to the filtering of tempolabile signal.
Description of drawings
Fig. 1 is the frequency response of four pseudo wavelet filtering devices of the present invention.
Fig. 2 is the shock response of four pseudo wavelet filtering devices of the present invention.
Fig. 3 is the frequency response of four wavelet filters.
Fig. 4 is the shock response of four wavelet filters
Fig. 5 is the pseudo-small echo direct transform of encoding and decoding of the present invention, inverse transformation synoptic diagram.
The embodiment of the codec among the present invention
The core technology description that the present invention encodes and implements
One, predicts the signal type determination strategy of carrying out based on adaptive threshold and typical sample
The present frame sequence is sent into the signal type judging unit, analyze the current demand signal type, change severe degree according to it and be divided into tempolabile signal and fast changed signal.
Two, the psychoacoustic model based on FFT calculates
In the present invention, utilize the forward masking effect of the sense of hearing, guaranteeing under the higher coding gain, effectively suppress " Pre echoes " phenomenon that causes because of the time domain lack of resolution.In transition coding, the selection of time domain frame length (being time domain window length) is restricted by the factor of two mutual contradictions: frame length is big more, and then coding gain is high more; And excessive frame length will make time domain resolution reduce, and produces serious " Pre echoes ".Therefore, selecting a suitable frame length, make the inhibition of coding gain and " Pre echoes " all reach the equilibrium point an of the best, is very important.Experiment showed, that when frame length shortens to 2ms～5ms because the forward masking effect, " Pre echoes " can be sheltered by the shock response of its back.For example, when 48kHz sampled, window length was 256 o'clock, and its time domain resolution is 5.3ms, because pre-masking effect, people's ear is discovered less than " Pre echoes ".
In the present invention, utilize masking effect, determine quantization level, the control quantizing noise makes it to be lower than or as far as possible near the masking threshold of people's ear, realizes undistorted audio coding and the subjective quality that improves audio coding under low code check.
Three, based on the time-domain filtering of pseudo-wavelet technique
It is 1024 frame that the input audio signal of pseudo-wavelet transformation evenly is divided into frame length, and pseudo-small echo direct transform and inverse transformation are that unit carries out with the frame.
Pseudo-wavelet transformation be input as 2048 time domain samples, be output as 1024 coefficients.Coding side reads in 1024 time domain samples of a frame from audio file at every turn, form pseudo-wavelet transformation input [former frame sample with 1024 time domain samples of former frame, present frame sample], carry out pseudo-wavelet transformation, export 1024 pseudo-wavelet coefficients, if present frame is first frame, then 1024 of former frame samples mend 0; If present frame is a last frame, promptly this frame back has not had time domain samples, and is full if this frame is then mended with 0 less than 1024 data, carries out conversion then; And after in the end frame coding is finished, also will mend a frame again and be entirely 0 additional frame, be former frame with the sample of last frame, forms input data [last frame, additional frame] and carry out pseudo-wavelet transformation, obtains 1024 coefficients.
Pseudo-wavelet inverse transformation be input as 1024 pseudo-wavelet coefficients, export 2048 output coefficients.Decoding end solves 1024 pseudo-wavelet coefficients of a frame at every turn from code stream, carry out pseudo-inverse wavelet transform then, 2048 inverse transformation coefficients that obtain, back 1024 inverse transformation coefficients of preceding 1024 inverse transformation coefficients and previous frame are superimposed, produce 1024 reconstruct time domain samples of present frame decoding, back 1024 coefficients keep the stack in order to next frame.After 1024 coefficients of first frame are made inverse transformation, produce 2048 output coefficients, preceding 1024 coefficients are lost, first section 1024 reconstructed sample of the superimposed generation of preceding 1024 the inverse transformation coefficients of back 1024 coefficients and second frame; After 1024 coefficients of last frame were done inverse transformation, back 1024 inverse transformation coefficients of preceding 1024 inverse transformation coefficients and previous frame were superimposed, produced 1024 reconstructed samples of final stage, and then 1024 inverse transformation coefficients are lost.
Four, handle based on the companding of (1) formula companding function
When the concrete enforcement of quantizing process, formula (1) parameter is desirable:
L=1, the parameter in the formula (2) can be made as
Five, the yardstick based on overall perceptual distortion minimum criteria quantizes
The detailed process that quantizes is:
A) pseudo-wavelet coefficient is divided into several scale factor bands by frequency band;
B) each scale factor band is chosen an initial gauges factor, make that the greatest coefficient in each scale factor band all is quantified as 0 (this moment, all pseudo-wavelet coefficients all were quantified as 0, and the masking by noise of each subband is than the signal-to-mask ratio that equals separately);
C) whether the masking by noise ratio of checking all subbands is all less than 1, if (it is transparent to show that all subbands have all reached perception), then end quantizes, otherwise, do steps d;
D) choose masking by noise than maximum subband, allow the scale factor of this subband increase by 1;
E) calculate the quantized result of this moment needed bit number of encoding, check whether required bit number surpasses target bit, if, showing that target bits has been assigned with finishes, then finish to quantize, otherwise, recomputate the masking by noise ratio of each subband, change step c.
This quantizing process can be in that to reach perception rapidly under the enough situation of code check transparent.From quantizing process as can be seen, quantized result just reached perception transparent in, quantizing process has just stopped.
This quantizing process also has the characteristics that optimal bit is distributed.Can prove, when doing to quantize according to (1) formula, not enough at code check, can not reach under the situation of transparent coding, this quantizing process can reach such optimal bit and distribute, it makes masking by noise ratio maximum in all scale factor bands reach minimum, that is to say that other any Bit Allocation in Discrete scheme that is different from this quantized result all can make masking by noise maximum in all scale factor bands than increasing.
Six, based on the adaptive H uffman entropy coding of characteristics of signals
The Huffman code table is made up of a series of code table, and entropy coder is selected optimum Huffman code table according to the statistical property of present frame sequence, carries out entropy coding, and generates the audio code stream of compression.
Basic coding process of the present invention
1,1024 time-domain signal samples of input one frame, the type of analysis current demand signal;
2, the time domain samples of the sample of signal of present frame and former frame is formed psychologic acoustics is calculated and the input of pseudo-wavelet transformation;
3, carry out pseudo-wavelet transformation, obtain 1024 pseudo-wavelet coefficients;
4, carry out psychologic acoustics and calculate, obtain the amount of sheltering parameter;
5,1024 pseudo-wavelet coefficients that just obtained are carried out noise setting and quantification treatment.
6, the scale factor of the integer quantization parameter that just obtained and each subband correspondence is carried out the Huffman coding, obtain the compressed bit stream of present frame.
7, code stream is outputed to ASCII stream file ASCII.
Basic decode procedure of the present invention
1, the order by cataloged procedure solves the quantization parameter of present frame and the scale factor of each subband correspondence from the compressed audio ASCII stream file ASCII.
2, determine the quantization step of each scale factor band according to the scale factor of each scale factor band, quantization parameter is carried out inverse quantization, obtain 1024 pseudo-wavelet coefficients.
3,1024 pseudo-wavelet coefficients are carried out contrary pseudo-wavelet transformation, obtain 2048 output coefficients, the latter half coefficient addition with in 2048 output coefficients of a first half output coefficient and former frame decoding obtains 1024 reconstruct time domain samples.
4, reconstructed sample is outputed to the reconstruct file.
Claims (1)
1, a kind of audio coding/decoding method based on pseudo wavelet filtering is characterized in that the signal processing method of scrambler is:
A) sound signal resolves into the frame that length is L, and does delay and handle;
B) the top frame sequence that obtains is sent into the signal type judging unit, analyze the current demand signal type, change severe degree according to it and be divided into tempolabile signal and fast changed signal;
C) according to the result of b,, calculate the auditory masking amount and calculate the pseudo wavelet filtering coefficient parallel psychoacoustic analysis unit and the pseudo wavelet filtering unit of sending into the corresponding types signal of present frame sequence;
D) pseudo-wavelet coefficient is organized by the subband order, and be divided into the scale factor band by its time-frequency characteristic;
E) the pseudo-wavelet coefficient after the re-organized is done companding and handle, the companding function is as follows
Wherein l is a positive integer, and α is the real number less than 1;
F) the pseudo-wavelet coefficient after companding is handled is sent into the quantifying unit of overall perceptual distortion minimum, the corresponding linear quantizer of each scale factor band, and quantitative formula is:
q(x)＝x′·2
β·scale_fac， (2)
L wherein, α is with (1) formula, and β is the real number less than 1, and scale factor scale_fac is a positive integer;
Quantizing process is for comprising a quantization loop, each circulation is to select current masking by noise than maximum scale factor band, give this subband minimum possible bit number distributing to additional allocation on the bit number basis of this subband originally then, and upgrade the masking by noise ratio of this subband; So circulation surpasses target bits until required bit;
G) with the Huffman scrambler of scale factor and quantization parameter input adaptive, scrambler is selected the Huffman code table according to the statistical property of present frame sequence, carries out entropy coding, forms the audio compression code stream;
The signal processing method of its demoder is:
I), solve the scale factor of present frame and the model type of quantization parameter and present frame with compressed bit stream input adaptive Huffman demoder;
Ii) with scale factor and quantization parameter input inverse DCT, calculate the pseudo-wavelet coefficient of inverse quantization, the formula of inverse quantization is
Wherein l, α, the same formula of β meaning (1), (2), q (x) and iq (x) are respectively quantization parameter and dequantized coefficients;
Iii) current frame signal type and the dequantized coefficients that just obtained are imported pseudo-small echo liftering unit, calculate the reconstruct time domain sequences;
Iv) the reconstruct time domain sequences that obtains is carried out delay compensation, calculate reconstruct time-domain audio sequence.
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| CN100349207C (en) * | 2003-01-14 | 2007-11-14 | 北京阜国数字技术有限公司 | High frequency coupled pseudo small wave 5-tracks audio encoding/decoding method |
| DE10345996A1 (en) * | 2003-10-02 | 2005-04-28 | Fraunhofer Ges Forschung | Apparatus and method for processing at least two input values |
| EP1581026B1 (en) * | 2004-03-17 | 2015-11-11 | Nuance Communications, Inc. | Method for detecting and reducing noise from a microphone array |
| WO2005096273A1 (en) * | 2004-04-01 | 2005-10-13 | Beijing Media Works Co., Ltd | Enhanced audio encoding/decoding device and method |
| EP1852851A1 (en) * | 2004-04-01 | 2007-11-07 | Beijing Media Works Co., Ltd | An enhanced audio encoding/decoding device and method |
| CN1317897C (en) * | 2004-09-28 | 2007-05-23 | 华中科技大学 | Parallel two-dimension discrete small wave transform circuit |
| CN101136202B (en) * | 2006-08-29 | 2011-05-11 | 华为技术有限公司 | Sound signal processing system, method and audio signal transmitting/receiving device |
| CN101312042B (en) * | 2007-05-23 | 2011-08-24 | 中兴通讯股份有限公司 | Quantizer self-adaptive regulation method for sensing audio encoding |
| CN101944361B (en) * | 2010-09-02 | 2015-09-02 | 北京中星微电子有限公司 | A kind of Bit distribution method and bit allocation |
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