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Description  |
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BACKGROUND OF THE INVENTION
1. Field of the Invention
The field of the invention is that of the compression of digital audio
signals. The invention can be applied notably to the transmission of sound
signals on digital channels as well as to devices for the storage of
digital sound signals.
More precisely, the invention concerns a bit allocation device enabling an
adaptive quantization of a digital audio signal, after this signal has
been transformed into the frequency domain and cut up into frequency
bands.
The invention may be implemented, for example, in direct satellite
broadcasing systems such as those developed in the European DAB (Digital
Audio Broadcasting) project, or again in ISDN broadcasting and high
fidelity distribution systems. It can also be applied notably to storage
devices such as digital disks.
Digital audio signals have many advantages over analog signals, notably as
regards the fidelity of the sound, the preservation of the initial quality
and flexibility of use. However, the bit rate resulting from the
conversion of the audio signals into digital form is very high, especially
for high quality signals, the bandwidth of which is greater than 15 kHz.
It is then necessary to use bit rate reduction techniques.
2. Description of the Prior Art
In a known and widespread way, the techniques used employ algorithms for
the mathematical transformation of the source digital audio signal. The
transform coding techniques have been extensively applied to the fields of
images or of speech. Since very recently, they are also applied to the
processing of audio (chiefly musical) signals.
In existing coders implementing these techniques, the signal is first of
all cut up into temporal blocks, and is then subjected to a time/frequency
transformation. It is the coefficients of the transformed blocks that are
encoded and transmitted. At the decoder, a reverse transformation delivers
the decoded and reconstructed signal.
The application of mathematical transformation achieves a concentration of
the energy of the source signal on the biggest coefficients, and thus
enables a reduction of the bit rate by controlling the auditive
degradation and reducing it to the minimum, notably by the selective
elimination of certain of the transformed coefficients. Indeed, the fact
of working in the frequency domain contributes towards taking account of
perceptual and psychoauditive properties that are mainly linked to the
spectral nature of the sound. The taking into account of the
psychoauditive criteria in most existing devices is based on the analysis
by ZWICKER in Psychoacoustique (Psychoacoustics), Masson, 1981, based on
the concept of the masking of inaudible spectral components.
The known devices made on the basis of these principles differ from one
another in certain preferences as regards their designing:
the transmission or non-transmission of a piece of auxiliary information
(side information) to the main information;
the use or non-use of techniques overcoming the effect of transmission
disturbances;
the techniques of taking account of the psychoauditive criteria to achieve
the bit rate reduction and the localization of their implementation in the
signal coding and decoding chains;
Thus, in a first known device of this type, as described in the French
patent document No. 89 06194, "Procede et installation a codage des
signaux sonores" (Sound Signal Coding Method and Equipment) filed on
behalf of the present Applicants, the following are implemented
successively: the cutting up of the sound signal into blocks of samples,
the time/frequency transformation and a predictive and adaptive coding of
the most significant coefficients of each block, using a stationarity of
the signal. In this device, the auxiliary information is transmitted
during transition blocks, thus making it impossible to take account of an
inter-block correlation. In all the other situations, this auxiliary
information is used solely to control the bit allocation module supplying
the main signal quantizer. This device enables a reduction in the bit
rate. However, it leads to a chain degradation of the reconstitution of
the blocks received when an error occurs, because this error gets passed
on to the next block, and so on and so forth, through the loop for
preparing the auxiliary information controlling the bit allocator and the
quantizer of the decoder.
There are also known devices in which a piece of auxiliary information is
transmitted for each block, by adaptive coding. Such a device is
described, for example, in the article by Bochow, "Multiprocessor
Implementation of an ATC Audio Codec" (Acts of the ICASSP Congress 1989,
Glasgow). A drawback of this device is that the continuous coding of the
auxiliary information calls for a high bit rate, to the detriment of the
bit rate allocated to the main information.
The document by Johnston, "Transform Coding of Audio Signals Using
Perceptual Noise Criteria", IEEE Journal on Selected Areas in
Communication", Vol. 6, No. 2, February 1988, pp. 314-323, has a bit
reduction device using adaptive quantization, with application of the
masking thresholds according to Zwicker's analysis in the form of a
prediction algorithm applied at the quantizer of the main signal. This
algorithm seeks to minimize the noise-to-masking threshold ratio. Just as
in Bochow's device, the auxiliary information is transmitted continuously.
Furthermore, this device has a variable length coding or Huffman coding at
output of the quantizer, which is quite complicated to apply.
The invention is aimed at overcoming the drawbacks of these different known
devices.
SUMMARY OF THE INVENTION
More precisely, the aim of the invention is to provide a device for the
compression of a digital audio signal, by using a device for the
allocation of bits available for the transmission or storage of the
signal, controlling means for the adaptive quantization of the signal, in
order to enable a major reduction in the bit rate while, at the same time,
preserving the quality of the starting signal to the maximum extent.
Another aim of the invention is to provide a bit allocation device such as
this, wherein the principle of operation takes account of psychoauditive
criteria.
Another aim of the invention is to minimize the chain degradation phenomena
at the reconstruction of the signal when a disturbance that generates
errors or interference occurs in the transmission channel.
A complementary aim of the invention is to provide, in one of the
advantageous embodiments of the invention, a principle for the joint
transmission of main information and auxiliary information by optimizing
the bit rate of the auxiliary information and then that of the main
information.
It is also the aim of the invention is to enable the use of a fixed number
of bits for the coding of each block of information.
These aims, as well as others that shall appear here below, are achieved by
means of a bit allocation device, of the type that enables the control of
means to quantize the compression of a transformed digital audio signal,
designed to be transmitted through a channel with a limited bit rate or to
be stored on a medium of digital information, wherein the allocation
consists notably in the assigning, to each band in a set of adjacent bands
covering the totality of the spectrum of the transformed signal, of a
number of specific bits for the expression of the transformed coefficients
of said signal, as a function of an auxiliary information corresponding to
a description of the spectrum of said transformed signal, said device
being informed by means for the prior elimination of spectral components
of said transformed signal as a function of a psychoauditive criterion.
This elimination of spectral components to prepare the auxiliary
information enables an a priori optimization of the quantization
operation.
Advantageously, said device includes (in a known way) means for computing
the masking threshold of spectral components on the basis of a
psychoauditive criterion, to optimize the allocation of the bits in each
of said bands.
Preferably, said psychoauditive criterion works according to Zwicker's
psychoauditive masking criterion.
According to a major characteristic of the invention, said means of
quantization include at least two distinct quantizers and means for the
selective assigning of one of said quantizers to each of said bands of the
spectrum of said transformed signal as a function of the number of
components preserved in said band, after said elimination of the masked
coefficients.
In a preferred embodiment of the invention, said device includes means for
minimizing a quantization noise-to-masking threshold ratio in each of said
bands.
Advantageously, said quantization noise is determined as a function of at
least one of the three pieces of information belonging to the group
including:
the standard deviation of said spectral components not eliminated in said
band;
a performance factor of said quantizer selected for said band;
a piece of information on the spectral spread of said band.
According to another characteristic of the invention, said piece of
information given by said means for the prior elimination of spectral
components is prepared by run length coding means for the coding of the
indices of said masked spectral components.
Preferably, said run length coding means use a variable length code of the
Huffman codes type.
According to an advantageous characteristic, said run length coding means
deliver a specific code word for the coding of the frequency bands all the
said components of which are eliminated.
Advantageously, said run length coding means are activated by selection
means, as a function of a piece of information on bit rate gain provided
by said coding.
According to another major characteristic of the invention, said device
cooperates with means for coding said auxiliary information corresponding
to the description of the spectrum.
In this way, it is possible to permanently transmit an auxiliary piece of
information without thereby causing major adverse effects on the main
information bit rate.
Preferably, said coding means include predictive coding means.
Thus, the risks of chain degradation are eliminated as regards the main
information. This degradation can occur, in the invention, only on the
auxiliary information.
Advantageously, said predictive coding means include means belonging to the
group comprising the logarithmic conversion means, the differential MIC
coding means and the means for coding by variable length codes of the
Huffman codes type.
Preferably, said coding means also include means for inter-block coding
without memory, said predictive coding means and said means for coding
without memory being selected according to a pre-determined criterion.
Advantageously, said pre-determined criterion is a least bit rate criterion
and/or a criterion for minimizing the effect of transmission errors.
According to an advantageous characteristic of the invention, at least one
of the pieces of information belonging to the group including said
auxiliary information corresponding to the description of the spectrum,
said information given by said means for eliminating the inaudible
components and a piece of information on spectral spread is transmitted or
stored jointly at each of the main information blocks.
According to another characteristic of the invention, said transformed
digital signal is prepared by tranform coding means using a transform of
the Princen and Bradley type of modified discrete cosine transform.
Advantageously, said transform coding means including means for the tapered
windowing of the temporal signal bringing out a symmetry in said
transformed signal.
Preferably, said windowing means use a window defined by:
##EQU1##
where N is the number of samples of said window.
BRIEF DESCRIPTION OF THE DRAWINGS
Other characteristics and advantages of the invention will appear from the
following description of a preferred embodiment of the invention, given as
a nonrestrictive example, and from the appended drawings.
FIG. 1 is a block diagram of the digital audio signal coding device,
including a bit allocation device according to the present invention.
FIG. 2 is a functional diagram of the module for the elimination of masked
lines.
FIG. 3 shows a detailed functional diagram of module for computation and
coding of the auxiliary information.
FIG. 4 is a functional diagram of the module for predictive coding of the
auxiliary information.
FIG. 5 is a diagram illustrating the principle of elimination of the masked
lines according Zwicker's analysis.
FIG. 6 shows a functional diagram of a module for selecting one among
several quantizers.
FIG. 7 is a functional diagram of a device for the allocation of bits to
each band.
DETAILED DESCRIPTION
The device of FIG. 1 enables the coding of digital audio data according to
the method of the present invention. The input signal x(n) 10, sampled at
a frequency greater than or equal to 32 kHz, is applied to the
transformation module 11. The sampling frequency corresponds to that used
for high fidelity sound.
A preferred embodiment of the transformation module 11 advantageously uses
the transform devised by Princen and Bradley, ("Adaptive Transform Coding
Incorporating Time Domain Aliasing Cancellation", in Speech Communication,
December 1987), also known as the modified discrete cosine transform
(MDCT). This transform corresponds to a projection on a cosine base. The
transform coefficients are defined by:
##EQU2##
with: N: size of the transform block
h(n): block weighting window
m: block transform number.
Its chief advantage is related to the fact that it permits the use of
high-performance weighting windows h(n) on the spectral plane, thus
achieving excellent separation of the transform channels. The
concentration of energy is then higher than with the discrete Fourier
transform (DFT) for example, and the coefficients to be coded are very
close to the true spectrum.
Before being transformed, the block of temporal samples is weighted by a
window h(n). A "tapered" window, for example a sinusoidal window is used,
defined by: h(n)=2 sin (.pi.(n+0.5)/N), n varying from 0 to N-1, N being
the number of samples per temporal block. The MDCT used works in perfect
synergy with this type of tapered window. Indeed, this type of window can
be used to obtain N/2 single coefficients after tranformation, the N/2
other coefficients being identical, except for the sign. On the contrary,
a rectangular window would lead to a spectral spread with respect to the
original signal. Since its application further calls for an inter-block
overlapping equal to 50% of the size of the blocks, the number of
transformed coefficients is identical to the original number of samples of
the source signal to be transmitted to each block. This inter-block
overlapping is necessary to enable the perfect reconstruction of the
signal.
The coefficients y(k) 12 leaving the tranformation module 11 are then
presented at the inputs of the various coding modules 13, 14, 15, 16, 17.
A first block carries out, first of all, the elimination of the inaudible
spectral components in the transformed signal 12.
This operation of elimination is based, for example, on Zwicker's analysis
as described in detail further below. This analysis makes it possible to
distinguish masked lines, corresponding to inaudible frequencies, in an
audio signal. The transform coefficients corresponding to these inaudible
components are not transmitted.
Since the MDCT is characterized by good frequency separation, the number of
lines eliminated may be great. The result thereof is a significant
reduction in the number of values to be transmitted. Furthermore, since
these untransmitted coefficients are generally of a low level, the
quantizers used for the transmitted coefficients may be optimized
accordingly.
The module for eliminating the masked lines 14 is more precisely described
further below, with reference to FIG. 2.
The spectral lines kept, given at the output of the module 14, form inputs
into the module 15 for the computation and coding of the auxiliary
information. The auxiliary information generated by the module 15 is
computed by frequency bands of unequal widths and may be coded by two
different modes. If the signal is stationary, the coding takes place with
respect to the preceding blocks (the interframe correlation is taken into
account), otherwise the current block is a transition block and the coding
takes place without taking account of the inter-block memory.
These coding means are described with greater precision further below, with
reference to FIG. 3.
The outputs of the module 14, for the elimination of the masked lines, and
of the module 15, for computing and coding the auxiliary information,
supply the bit allocation module 16 controlling the quantizer 17. The
output of the bit allocation block 16 gives a piece of information 18 on
the number of bits R available for the expression of each of the
coefficients y(k) of the transformed signal 12. This bit allocation is
dynamic: it varies from one block to the next one. Moreover, it is
designed to provide for the masking of the quantization noise.
The bit allocation module 16 also has, for its input, the values of the
spectral spread function measured in frequency bands given by a module 13
for the computing and coding of the spectral spread, on the coefficients
of the transformed signal 12. This enables the nature of the spectrum,
notably the fact of whether it is highly concentrated or not, to be
characterized.
The working of the bit allocation module 16 is developed further below.
Finally, the coefficients y(k) of the signal 12 are quantized in the module
17 according to the piece of information 18 on the allocated number of
bits R. Furthermore, according to a major characteristic of the invention,
the piece of information 19 obtained at output of the coder 15 of the
auxiliary information as well as the information on the elimination of the
masked lines coming from the module 14 enable the choice, for the current
block, of one among several available quantizers, as shall be seen
hereinafter.
The decoding is done in a manner that is quite symmetrical with the coding.
FIG. 2 shows the functional diagram of the masked line elimination module
14.
The function of this module is to eliminate the lines that are inaudible
because of masking phenomena, so that only perceptually useful information
is transmitted.
This procedure is particularly useful for wide spectrum sounds, rich in
harmonics. A large number of coefficients is then masked. It is precisely
this type of signal that requires a higher bit rate, because of the
quantity of information to be transmitted.
This device includes a masked line detection module. This detection
concerns the real spectrum and is done only by a coder. It makes use of
the frequency masking curves, according to Zwicker's analysis. As shown in
FIG. 5, it would appear that, for each line 51 transmitted, the lines that
are beneath a line 52 of -25 dB per critical band upstream of the line and
beneath a line 53 of -10 dB per downstream critical band, are inaudible.
These two slopes correspond respectively to the anterior and posterior
frequency maskings.
The spectrum is divided into 24 critical bands, B.sub.1, B.sub.2, B.sub.3
and multiplied by the ear transmission factor a.sub.o for each of said
bands.
The computation of the masking threshold is separated into "critical
intraband" masking and "critical inter-band" masking.
The intra-band masking corresponds to the total masking effect of all the
lines 51.sub.1, 51.sub.2 within one and the same band B.sub.2. The
intra-band masking threshold is computed by summation of the contribution
of each coefficient y(k) of the transformed signal.
If we consider the critical band j, demarcated by b.sub.b (j), the lower
limit, and b(j), the upper limit, the contribution of the coefficient y(k)
to the intra-band masking threshold s.sub.in (j) is given by:
s.sub.in.sup.k (i)=.theta..(y(k).sup.2.a.sub.o (j))
with b.sub.b (j).ltoreq.i.ltoreq.k-3 and k+3.ltoreq.i.ltoreq.b.sub.h (j)
where .theta. is a constant shift corresponding to -30 dB.
As can be noted, each coefficient y(k) does not affect the masking
threshold of the four nearest coefficients. This precaution is necessary
to prevent untimely zero-settings that might occur around peaks of the
spectrum.
The masking threshold is finally obtained by summation of the
s.sub.in.sup.k (i):
##EQU3##
with b.sub.b (j).ltoreq.i.ltoreq.b.sub.h (j) and j=1, . . . , 24.
The inter-band masking results from the taking into account, in each band
B.sub.2, of the masking effect of the adjacent bands. In fact, only the
posterior masking (that of the lines 51.sub.3 of the band B.sub.2) is
considered for the computation of the inter-band masking threshold. The
anterior masking (band B.sub.1) is too low to substantially modify the
number of masked lines per block (-25 dB per critical band instead of -10
dB).
The contribution s.sub.out j(i) of each critical band j to the masking of
the following bands (i>j) is computed by:
##EQU4##
The total inter-band masking, for the critical band i, is equal to:
##EQU5##
Finally, for the coefficient y(i), of the critical band j, the final
masking threshold is obtained by summation:
s(i)=s.sub.in (i)+s.sub.out (j).
The energy of the coefficient y(i), multiplied by the transmission factor
a.sub.o (j) is then compared with the masking threshold thus defined. If
a.sub.o (j).y.sup.2 (i)<s(i), the coefficient y(i) is supposed to be
masked.
This function is fulfilled by the sub-module 21 of FIG. 2. This figure
gives a detailed view of the main constituent sub-modules of the masked
line eliminating module 14 of FIG. 1.
Advantageously, the detection of the masked lines in the sub-module 14 is
followed by a coding of the indices of the masked lines, done by the block
20. This coding is necessary to indicate the numbers of the masked
coefficients to the decoder and uses, for example, the run length coding
technique.
Let I.sub.m (k) be a bit equal to 1 if the coefficient y(k) is masked. The
series {I.sub.m (k),k=0, . . . , N/2} has uninterrupted runs of 0 and 1,
of varying length, formed in a sub-module 22. It is the length of the runs
that are transmitted by means of a variable length code 23. If very many
lines of the same state follow one another without discontinuity, then the
bit rate to be allocated to this auxiliary information may be low.
The variable length coding of the sub-module 23 is done advantageously by a
Huffman code computed from a density of experimental probability.
The coding of the runs starts only from the first masked line onwards. The
number of this masked line is transmitted on 9 bits.
At the coder, the run length coding consists simply in making a search for
all the runs of 0 and 1 and in associating the corresponding Huffman code
word with them.
The length of the runs is limited to maximum values: 64 coefficients for
the 0 runs and 128 coefficients for the 1 runs. If these limits are
exceeded, a run having zero length and the reverse state is transmitted.
With this zero length run, there is associated a Huffman code word which
is itself also computed (outside the line) after the occurrence of the
run.
At the decoder, after reception of the first masked line, it is enough to
decode the Huffman codes. The runs of codes of lengths 0 and 1 enable the
series {I.sub.m (k)} to be reconstituted exactly.
If the runs of 0 and 1 are greatly fragmented, the auxiliary information
bit rate may be high. For a small number of masked lines, the gain of
their non-transmission may be zero, or even negative. It would then be
appropriate not to proceed with this non-transmission or, at least, to
restrict it to certain frequency zones.
To this end, the mean number of bits per coefficient is computed in both
the following cases:
transmission of all the coefficients:
R.sub.1 (k)=(R.sub.0 -R.sub.ifs)/(N/2)
where
R.sub.0 is the total number of bits per block,
R.sub.ifs is the number of bits necessary for the transmission of the
auxiliary information describing the spectrum. R.sub.ifs is actually the
value of the preceding block.
non-transmission of the masked lines by the use of run length coding:
R.sub.2 (k)=(R.sub.0 -R.sub.ifs -R.sub.im)(N/2-N.sub.rm)
where
R.sub.im is the auxiliary bit rate of the run length coding,
N.sub.rm is the number of masked lines.
The non-transmission of the masked lines is done for the entire band
considered if the test and bit rate computing sub-module 24 establishes
that:
R.sub.im <N.sub.rm.(2(R-R.sub.ifs)/N).
If this condition is not met, this test is done in four frequency sub-bands
of the band considered, having equal widths. during the search for the 0
and 1 runs, the "local" values R.sub.im (l) and N.sub.rm (l) (l=1, . . . ,
4) are computed.
If R.sub.im (l)<N.sub.rm (l).(2(R.sub.0 -R.sub.ifs)/N), that is, if the
gain in bits is positive for the frequency sub-band 1 considered, the run
length coding is applied to the coefficients of this sub-band l.
If not, the coefficients of this band are considered to be non-masked and
the index of the first coefficient enforced to 0 is modified accordingly.
The coding validation sub-module 25 controls the variable length coding
sub-module 23, depending on whether or not it is necessary to to perform
the coding.
The mean auxiliary bit rate is of the order of 0.8 bits per masked line.
This low value proves that it is worthwhile to use run length coding.
FIG. 3 shows the detailed functional diagram of the module 15 for the
computation and coding of the auxiliary information.
The transmission of a piece of auxiliary information is necessary to
compute the bit allocation and to quantize the coefficients. This
auxiliary information 19 is actually a variably precise descriptor of the
spectrum of the signal.
In the embodiment described, the spectrum descriptor is computed in a
sub-module 31 in frequency bands of unequal length. The spectrum is
divided, for example, into 50 frequency groups.
The limits b.sub.si.sup.b (j) and b.sub.si.sup.h (j) of these bands are in
keeping with those of the critical bands. The narrowest bands (j=1, . . .
, 14) have the same width as the corresponding critical bands. The other
bands having an increasing width which reaches 562.5 Hz (i.e. 18
coefficients) for the last band (j=50).
The spectrum descriptor used .sigma.(j) is equal to the standard deviation
of the non-masked spectral lines in each of the bands
##EQU6##
with j=1, . . . , 50 N.sub.si (j) is the number of non-masked coefficients
in the band j.
The originality of the coding of this information, according to the
invention, lies in the fact that the correlation existing between the
successive transform blocks is taken into account by means of a predictive
coding. Thus the coder derives advantage from all the correlations of the
signal (in the short term and in the longer term).
The coding of the auxiliary information is usually done without taking
account of the perceptual properties, unlike in the case of the
quantization of the coefficients. It is necessary, however, to reserve the
greatest number of bits possible for the bit rate of the main signal 101,
and hence to reduce the bit rate of the auxiliary information 19.
A direct coding of the components of the spectrum descriptor .sigma.(m,j)
(m=block number) calls for a high bit rate. However, since the signals are
generally highly stationary, the spectrum descriptor is highly correlated
from one block to the next one.
The most direct way to benefit from this stationary quality is to carry out
a predictive coding 32. Owing to the great spectral dynamic range, it is
preferable to apply the prediction to to .sigma.(m,j) expressed in dB.
Indeed, it is the ratio .sigma.(m,j)/.sigma.(m-1,j) rather than the
difference .sigma.(m,j)-.sigma.(m-1,j) that has a high predictive gain.
As shown in FIG. 4, this predictive coding has an operator 41 for
conversion into a logarithmic scale followed by a Differential MIC Code
and a variable length coding device 43.
The prediction is done by a first-order predictor 44. The coefficient of
prediction a.sub.1 may take a value between 0.95 and 1. The input of this
predictor 44 is the previous quantized value log (.sigma.'(m,j)).
The prediction error
e(m,j)=log (.sigma.(m,j))-a.sub.1. log (.sigma.'(m-1j))
with j=1, . . . , 50
is quantized by a uniform quantizer 45 having, for example, 32 levels for a
dynamic range of [-2,2].
Since the signal is stationary for lengthy periods, the density of
probability of the code words at output of the quantizer 45 is highly
concentrated. As a consequence, these code words undergo a variable length
coding 43 (Huffman coding) which enables the bit rate of transmission of
the spectrum descriptors to be reduced to about 2.5 bits per value
.sigma.'(m,j).
The value log (.sigma.'(m,j)) is obtained by the summation 46 of the value
given by a reverse quantizer 47, corresponding to the value that will be
obtained at the decoding, and of the previous value coming from the
predictor 44.
If a frequency band is entirely masked (N.sub.si (j)=0), it is not
necessary to transmit a code word for the band j. Indeed, the value of
.sigma.(m,j) is, in this case, known to the decoder by means of the
information concerning the masked lines.
However, to prevent a transmission error on the bits I(m,k) from being
passed on to the values .sigma.'(m,j), a redundancy is deliberately
introduced into the coding: if N.sub.si =0, a specific code word is
transmitted, computed as a function of its occurrences, like the other
code modes.
Thus, when the band ceases to be entirely masked, the prediction relates to
the last non-transmitted non-zero value .sigma.'(m-p,j).
During the spectral transitions (non-stationarity of the signal), this
quantization procedure is no longer valid for it demands an excessively
high bit rate to keep the same precision of quantization. It is then
necessary to make use of a coding without memory of .sigma.(m,j), applied
in the sub-module 34.
This second coding 34 is similar to the preceding one. The prediction takes
place frequentially instead of being done on successive transform blocks.
The prediction error is computed by:
e(m,j)=log (.sigma.(m,j))-log (.sigma.'(m,j-1)).
e(m,j) is coded by a uniform quantizer having, for example, a dynamic range
of 100 dB and 50 levels of quantization. The code words at output also
undergo a Huffman coding.
The first value of .sigma.(m,1) is transmitted separately.
A module 33 for 94 choosing the type of coding selects the best coding
according to the number of bits expended. If the bit rate necessary for
the interframe coding exceeds a threshold fixed beforehand, the second
type of coding 34 is used. This choice is transmitted to the decoder by
means of a decision bit.
It is also possible to take account, for the selection of the type of
coding, of another criterion than that of the minimization of the bit
rate. It is possible, for example, to act so as to minimize the effect of
the transmission errors.
The predictor 44 is a first order auto regressive predictor (AR(1)), with a
prediction coefficient close to 1. Consequently, there is a risk that the
transmission errors might get propagated indefinitely. Since the auxiliary
information has a major importance, inter alia for the allocation of the
bits, it is necessary to reinitialize the inter-frame coding. To this
effect, for all the blocks of a rank that is a multiple of 16, inter-block
coding without memory is used, even if the signal is stationary.
The coefficients y(k) 12 are coded by means of non-uniform adaptive
quantizers. The adaptation is done by the quantized spectrum descriptor
.sigma.'(m,j), where j is the number of the band to which y(k) belongs.
Each value .sigma.'(m,j) represents a variable number, N.sub.si (j), with
non-zero coefficients, because of the variable width of the frequency
bands and of the device for detecting the masked lines. The performance
values of the quantizers vary as a function of the number of coefficients
to be quantized N.sub.si (j).
According to the invention, and so as to optimize the coding system,
several sets of quantizers are available, as a function of N.sub.si (j).
FIG. 6 shows the functional diagram of the module for selecting the
quantizer to be used.
For example, in the following configuration, five sets 61.sub.1 to 61.sub.5
of quantizers are available. A module 62 for testing the value N.sub.si
(j)=1 controls a selector 63 according to the following criteria:
the first set for bands having one non-zero coefficient: N.sub.si (j)=1
the second set for: N.sub.si (j)=6
the third set for: 6>N.sub.si (j)>2
the fourth set for: 10>N.sub.si (j)>5
the fifth set for: N.sub.si (j)>9.
In each case, optimum quantizers for a number of bits varying, for example,
between 1 and 6 bits, has been computed. A second selector 64 enables a
choice to be made, in each set of quantizers 65.sub.1 to 65.sub.6, of the
optimal quantizer as a function of the number of bits R 18. Thus, the
optimization of the choice of the quantizer is achieved as a function of
the number of coefficients to be quantized and the number of bits
allocated by the bit allocation module.
FIG. 7 shows the device for allocating bits to each band according to the
invention.
The allocation of the bits is designed to accomplish the spectral shaping
of the quantization noise according to perceptual criteria. It minimizes
the noise to masking threshold ratio. This procedure is carried out at the
decoder and is based on the spectrum descriptor transmitted beforehand.
The allocation of the bits includes a module for computing the masking
threshold S(k) (this computation is similar to the one performed for the
detection of the masked lines) and a module 72 for quantizing the ratio
.alpha.(k)..beta.(k)..sigma..sup.2 (k)/S(k) comparable to the one
described by Yannick Mahieux in the article, "Transform Coding of Audio
Signals Using Correlation Between Successive Transform Blocks" (Acts of
the ICASSP Congress, Glasgow, 1989).
.sigma..sup.2 (k) is the square of the spectrum descriptor, extended to all
the coefficients y(k) of the band. It concerns the essential element of
the ratio to be quantized. Since the coefficients are coded with different
sets of quantizers (according to N.sub.si (j)), it is necessary to include
the relative performance values of each set of quantizers in the
allocation of the bits, according to the work by Jayant and Noll, Digital
Coding of Waveforms (Prentice Hall Signal Processing Series, 1984).
The function .alpha.(k) is equal to the performance factor of the quantizer
to be used for the coefficient y(k). A table 73 includes, for example,
five values of .alpha.(k) computed beforehand. This table is addressed by
the number of non-zero coefficients. Taking account of the real
performance values of the sets of quantizers enables a very appreciable
improvement in the quality of the coding.
The module 74 for computing the function .beta.(k), for its part, takes
account of the spectral spread .gamma., also according to Jayant and Noll.
This function indicates whether the spectrum is concentrated or not, and
is computed at the coder by:
##EQU7##
For the allocation of the bits, .gamma. is computed in four frequency bands
of equal width. These four values are transmitted to the decoder by means
of a uniform quantization on 6 bits.
In each of these four frequency bands, the function .beta.(k) is computed
according to the value of .gamma. by means of a non-linear function. The
role of .beta.(k) is to force the allocation of the bits to grant a
greater number of bits to the zones of the spectrum that contain peaks.
Indeed, the coefficients y(k) corresponding to the pure sounds contained
in the signal should be coded with higher precision, the masking threshold
then having a level, as compared with that of the signal, that is lower
than in the case of a noise spectrum.
The explicit detection of the inaudible spectral components, as well as the
use of the inter-block correlation, enables a reduction in the bit r | | |
