EP1794748A1 - Data processing method by passage between different sub-band domains - Google Patents

Abstract

The invention concerns data processing by passage between different subband domains, of a first number L to a second number M of subband components. After determining a third number K, least common multiple between the first number L and the second number M: a) if K is different from L, it consists in arranging in blocs, by a serial/parallel conversion, an input vector X(z) to obtain p <SUB>2</SUB>

Description

 Method of processing data by passing between different subband domains

The present invention relates to data processing by passing between different subband domains, including, but not exclusively, for transcoding between two types of compression coding / decoding.

Recent developments on the digital coding formats of multimedia signals now allow significant compression rates. In addition, the increase in the capacity of the transport and access networks now ensures a widespread use by the general public of digital multimedia content (speech, audio, image, video and other). The consumption of this content is done on various types of terminals (computers, mobile terminals, personal assistants (PDAs), Set-Top Boxes, or other) and via different types of network (IP, ADSL, DVB, UMTS, or others). This access to multimedia content by the user must be done transparently on these different terminals and through these different networks. This is referred to as "universal access to multimedia content" or "UMA" for "Universal Multimedia Access", a schematic illustration of which is shown in FIG.

One of the main problems due to the heterogeneity of terminals concerns the diversity of coding formats that they are able to interpret. One possible solution would be to recover the capabilities of the terminal before delivering the content in a compatible format. This solution may be more or less effective depending on the delivery scenario of the multimedia content considered

(download, streaming or broadcast). It becomes inapplicable in some cases, as for the diffusion

(or "broadcasting") or for streaming in multicast mode. The notion of transcoding (or changing the encoding format) is therefore important. This operation can take place at different levels of the transmission chain. It can intervene at the server to change the format of content previously stored for example in a database, or intervene in a gateway in the network, or other.

A common and straightforward method of transcoding is to decode the content and recode it to obtain a representation in the new encoding format. This method generally has the drawbacks of using a large computing power, of increasing the algorithmic delay due to the processing and sometimes of adding further degradation of the perceptual quality of the multimedia signal. These settings are very important in multimedia applications. Their improvement

(Decrease in complexity and delay and maintenance of quality) is an important factor of success for these applications. This factor sometimes becomes an essential condition for implementation.

In order to improve these parameters, the "intelligent" transcoding principle is born. This type of transcoding consists in performing a partial decoding, as minimal as possible, of the initial coding format to extract the parameters allowing the reconstruction of the new coding format. The success of this process It is therefore able to reduce algorithmic complexity and delay and to maintain or even increase perceptual quality.

In image and video coding, several work on transcoding has been done. Examples include changing the image size from CIF to QCIF, or MPEG-2 to MPEG-4. For the transcoding of speech signals, typically in telephony, work is in progress to solve problems related to coding formats. In addition, very few, or almost no, works have addressed the processing of audio signals. The existing work remains limited to the case of the reduction of the bit rate within the same format or the passage between certain coding formats of very close structures. The main reason lies in the fact that the most used audio encoders are of transform type (or sub-bands) and, generally, these encoders use different transforms or banks of filters. Thus, it will be understood that the realization of a conversion system between the representations of the signal in the domains of these transforms or banks of filters is therefore the first difficulty to overcome before being able to tackle any other problem related to intelligent transcoding in the field of audio.

The following is a definition of audio transcoding and the main problems that arise after a brief review of the principles of perceptual audio coding in subbands. There is a wide variety of audio coders that have been designed for different types of applications and for a wide range of flow rates and qualities. These encoders can be manufacturer-specific (or "proprietary"), or standardized by decision of international organizations. In addition, they all have a common basic structure and are based on the same principles.

The basic principle of perceptual frequency audio coding is to reduce the flow of information by exploiting the properties of the human hearing system. The irrelevant components of the audio signal are eliminated. This operation uses the phenomenon called "masking". Since the description of this masking effect is mainly in the frequency domain, the representation of the signal is carried out in the frequency domain.

More concretely, the basic schemes of a coding and decoding system are shown in Figures 2a and 2b. Referring to FIG. 2a, the input digital audio signal Se is first decomposed by an analysis filter bank 20. The resulting spectral components are then quantized and then coded by the module 22. Quantization uses the result of a perceptual model 24 so that the noise that results from the treatment is inaudible. Finally, a multiplexing of the different coded parameters is performed by the module 26 and an audio frame Sc is thus constructed. With reference to FIG. 2b, the decoding is done in a dual manner. After demultiplexing the audio frame by the module 21, the various parameters are decoded and the spectral components of the signal are de-quantized by the module 23.

Finally, the temporal audio signal is reconstituted by the synthesis filterbank 25.

The first stage of any perceptual audio coding system therefore consists of an analysis filter bank 20 used for the time / frequency transformation. A wide variety of filter banks and transforms have been developed and exploited in audio coders. As an example, pseudo-QMF filter banks, hybrid filter banks, and MDCT transform banks can be mentioned. The MDCT transform is currently proving to be the most effective in this context. It is the basis of the latest and most advanced audio coding algorithms such as those used for MPEG-4 AAC, TwinVQ and BSAC, Dolby AC-3, in the TDAC encoder / decoder (for "rhyme Domain Aliasing Canceling"). ) of France Telecom, in ITU-T G.722.1.

Although these different transformations have been developed separately, they can be described by a similar general mathematical approach and from different points of view: Modulated cosine filter banks, orthogonal transforms (or "LOT" for "Lapped Orthogonal Transform ") and more generally for the banks of maximum decimation filters, that is to say to critical sampling. It is recalled that Critical sampling property for a filter bank is that the subsampling / oversampling factor is equal to the number of subbands.

FIGS. 3a and 3b respectively illustrate the conventional transcoding and intelligent transcoding schemes in a communication chain, between a coder CO1 according to a first coding format and a decoder DEC2 according to a second coding format. In the case of conventional transcoding, it is a question of carrying out a complete decoding operation by the decoder module DECl according to the first format (FIG. 3a), followed by recoding by the encoder module C02 according to the second format, to finally arrive at the second coding format.

In the case of Figure 3b, it is instead to replace the two blocks DECl and C02 of Figure 3a by an integrated module 31 so-called "intelligent" transcoding module.

FIG. 4 shows the details of the operations that are merged by the implementation of intelligent transcoding. It mainly involves integrating the functional blocks of the synthesis filter banks BS1 and the BA2 analysis filter banks of the conventional transcoding into a system for direct conversion between subband domains in the module 31.

The use by encoders of different types of filterbanks (of sizes, particularly in terms of number of subbands, and different structures) is the first and main problem to overcome. It is therefore a question of transposing all the samples of a frame of the domain of an initial bank of filters to that of a bank of filters of destination. This transposition is the first step in any intelligent audio transcoding system.

Table 1 below gives a summary of the types of filter banks used in the most well-known transform audio coders, as well as their characteristics. As can be seen, in addition to the MDCT transform which is the most used, there are Pseudo-QMF benches. Moreover, they are all part of the family of maximum decimation banks and modulated cosines verifying exactly or almost the perfect reconstruction property.

Table 1: The most used filter banks in audio coding and their characteristics.

Encoder Filter Bank Features

MPEG-I Layer Pseudo-QMF Number of bands M = 32

I & II

MPEG-I Layer Pseudo-QMF / MDCT 32 bands followed by an MDCT of

III (hybrid) size 18 for each

MPEG-2/4 AAC MDCT M = 1024 bands for the long window and M = 128 for the short window.

KBD window (Kaise-Bessel

Derived) with a = 4 for stationary states and α = 6 for transitions.

It is indicated that the transition between AAC and AC-3 formats is currently of great interest.

Table 2 below shows some types of subband coding in Table 1, detailing some of their applications. Table 2: Examples of subband coders for audio and speech signals and some examples of their main applications.

In the known prior art in audio transcoding, US-6,134,523 discloses a rate reduction method in the coded domain for audio coded in MPEG-I Layer I or II signals. Although this method is similar to audio transcoding methods, it does not make any change between coding formats and the signals of the subbands remain in the representation of the same transformed domain, namely the representation of the pseudo filter bank. QMF. Here, the signals are simply re-quantized according to a new bit allocation. Moreover, in US-2003/0149559, a method is proposed for reducing the complexity of the psycho¬ acoustic model during a transcoding operation. Thus, in order not to resort to a masking threshold calculation operation during a transcoding, the new system uses values stored in a database of distortion jigs. Even if this method deals with a problem of transcoding, it remains far from the objectives relative to the passage between filter bank domains.

In document US-2003/014241, a transcoding system is proposed between the MPEG-I Layer II and MPEG-I Layer III audio coding formats. Indeed, the MPEG-I Layer II format uses a pseudo-QMF analysis filter bank and the MPEG-I Layer III format uses the same filter bank followed by an MDCT transform of size 18 applied to the signals of the subsystems. output bands of the latter. We are talking about "hybrid filter bank". The conversion system proposed in this document consists in applying this transform after inverse quantization of the subband samples of an MPEG-I Layer II frame. The system thus benefits from the similarity between the two coding formats.

With regard to the object of the present invention, the following remarks can be noted:

This technique of the prior art can be applied only for this particular case of transcoding. • This technique does not really treat a conversion to a different new subband field. It's just a matter of cascading a new Missing analysis filter bank, which allows to increase the frequency resolution.

In another context of image data processing and / or video, multi-choice filtering and processing in the transformed domain is already known, in particular by the reference: ⁿ 2 -D Transform-Domain Resolution Translation ", J.- B. Lee and A. Eleftheriadis, IEEE Trans., Circuit and Systems for Video Technology, Vol 10, No. 5, August 2000.

It describes a generalization of a method of linear filtering in the transformed domain (TDF for "Tranform Domain Filtering"). More particularly, this generalization is established in the case where the first transform (inverse) T ₁ , and the second transform (direct) T ₂ , are of the same sizes. Generalization consists first of all in extending the method in case the transforms are not of the same size. This method is then called "non-uniform TDF" (or NTDF). It is then extended to the case where, in addition to the filtering, multi-choice processing operations (subsampling and sampling) are added to the transformed domain, which results in the Multirate-TDF (MTDF).

As an application, the Transform-Domain Resolution Translation (TDRT) is proposed, especially for image and video applications (conversion between CIF and QCIF image formats) where the transform is a DCT (for "Discrete Cosine Transform"). This reference is only interested in filtering in the domain transformed. The exposed method is restricted only to the case of non-overlapping transforms such as a DCT, a DST, or the like, but could not typically be applied to overlaid transforms such as an MLT (for "Modulated Lapped Transform") and more generally, to any type of filter bank with maximum decimation, these filters can further be finite impulse response or infinite.

With regard to the conversion between DCT domains of different sizes, still for the transcoding of images and video, one can quote the reference:

"Direct Transform to Transform Computation", A. N.

Skodras, IEEE Signal Processing Letters, Vol. 6, No. 8, August 1999, Pages: 202-204.

In this document, a method of switching between DCT transforms of different sizes for sub-sampling of images in the DCT domain is proposed. One of the applications of this method would be transcoding. Moreover, this method is restricted to the construction of a transformed vector of size N from two adjacent transformed vectors each of size N / 2.

A conversion method between the representations of the signal in the MDCT domain and the DFT (Discrete Fourier Transform) domain is presented in document US 2003/0093282.

It was developed for the purpose of converting the audio signal into a representation where it can be easily modified. Indeed, TDAC filter banks are more convenient and more used in audio encoders, unlike DFT filter banks. Moreover, to carry out a processing or modifications on the signal components in this transformed domain is neither adequate nor sufficiently flexible given the existence of the aliasing components. On the other hand, the DFT representation is more useful when it comes to making changes to the audio signal such as a time scale change or a pitch shift. This reference therefore proposes a direct conversion method between MDCT domain and DFT instead of applying the conventional method of synthesizing the time signal by an inverse MDCT, and then applying the DFT. This method makes it possible to carry out modifications directly in the coded domain. The document also proposes the dual conversion method between the DFT and MDCT domains that would be useful in case there is a need to recode the audio signal after modification.

In this reference, the comparison in terms of complexity with a conventional conversion method shows no reduction. In addition, a small gain in memory for storing data is demonstrated.

However,

• The method in this reference deals with a particular case. It is restricted to the only case of conversion between the MDCT and DFT domains and vice versa. • The method is restricted in case these two filter banks are of the same size. We also quote the publication:

¹¹ An Efficient VLSI / FPGA Architecture for Combining an Analysis Filter Bank following a Synthesis Filter Bank ¹¹ , Ravindra Sande, Anantharaman Balasubramanian, IEEE International Symposium on Circuits and Systems, Vancouver, British Columbia, Canada, May 23-26, 2004.

This publication discloses an efficient structure for implementing a synthesis filter bank system, at L sub-bands, followed by an M sub-band analysis filter bank, where M and L are multiple. one of the other. This structure is effective for implementation in VLSI ("Very Large Scale Integration") or FPGA ("Field Programmable Gate Array") or parallel processors. It requires fewer logic blocks, low power consumption and allows the degree of parallelism to be extended. The proposed method is applicable in situations where subband-based processing follows another subband treatment and where the synthesized intermediate signal is not needed.

However:

• The method described above makes the restrictive assumption that the filter banks considered are modulated and can be decomposed into a polyphase structure.

• The method is restricted to special cases where M and L are multiples of each other.

It should also be stated that the structure of the conversion scheme between subband domains is some similarity with that of the trans-multiplexing problem presented in particular in:

"MuItirate Systems and Filter Banks", P. Vaidyanathan, Prentice Hall, Englewood Cliffs, NJ, 1993, pp.148-151.

Indeed, in TDM to FDM trans-multiplexing (for "Time Domain Multiplexing" to "Frequency Domain Multiplexing"), a synthesis filter bank is used. To reconstruct the interleaved time signals (that is to say perform the operation of reverse multiplexing from FDM to TDM), an analysis filter bank is used. The structure of the TDM->FDM-> TDM system thus amounts to a cascading of a synthesis filter bank and an analysis filter bank, which corresponds to what is also used in a system. conventional transcoding. The problem generally posed in these trans-multiplexing systems is to reconstruct the original signals without distortions after the TDM->FDM-> TDM operation. This is mainly to eliminate the distortions due to the phenomenon of crosstalk (or "cross-talk") that result from the use of non-perfect bandpass filters, in these banks of filters. A judicious design of the synthesis and analysis filters, as indicated in the same reference: "Multirate Systems and Filter Banks", PP Vaidyanathan, Prentice Hall, Englewood Cliffs, NJ, 1993, pages 259-266, overcomes this problem. problem. In the design proposal of these filters, a method is given for merging the synthesis and analysis filter banks, which amounts to proposing an intelligent conversion system. However:

• In the multiplexing structure proposed in this document, the synthesis and analysis filter banks have the same number of bands [M = L].

• It is not intended to build a trans-multiplexing system that merges the synthesis and analysis filter banks exactly as in transcoding. These two filter banks are cascaded independently.

The present invention improves the situation with respect to the state of the art presented above.

To this end, it proposes a method implemented by computer resources for processing data by passing between different subband domains, consisting in compacting in the same process the application of a first vector comprising a first number L of components. in respective sub-bands, to a synthesis filterbank, then to an analysis filter bank, to obtain a second vector having a second number of M components in respective subbands.

The method according to the invention comprises the following steps, after determining a third number K, the least common multiple between the first number L and the second number M: a) if the third number K is different from the first number L , put in blocks by a conversion series / parallel of the first vector to obtain p ₂ polyphase component vectors, with p ₂ ≈K / L, b) application of a chosen matrix filtering, involving a square matrix T (z) of dimensions KxK, to said p ₂ component vectors polyphase to obtain p _λ polyphase component vectors of the second vector, with P ₁ = KfM, and c) if the third number K is different from the second number M, set in blocks by parallel / serial conversion to obtain said second vector.

Thus, the present invention proposes in particular, but not exclusively, as will be seen below, a transcoding of a first type of coding, any, to a second type of coding, any. It will also be understood that the respective numbers of M and Z sub-bands are any natural numbers and are not necessarily linked by a proportionality relation, in the most general case.

Thus, the method in the sense of the invention can advantageously be applied to the transcoding of a first type of encoding / decoding in compression to at least a second type of encoding / decoding in compression. This application typically consists in compacting in the same treatment the following steps:

recovering data at least partially decoded according to said first type, in the form of a first vector comprising a first number L of components in respective sub-bands, applying the first vector to a synthesis filter bank according to the first type, then to an analysis filter bank according to the second type, and

recovering a second vector comprising a second number of components M in respective subbands and capable of being applied to subsequent coding steps according to the second type.

The present invention also relates to a computer program product, intended to be stored in a memory of a device in a communication network, such as a server, a gateway, or a terminal, and then including instructions for the implementation of of all or part of the process according to the invention.

The present invention also relates to equipment such as a server, a gateway, or a terminal for a communication network, and comprising computer resources for implementing the method according to the invention.

Other features and advantages of the invention will appear on examining the detailed description below, and the accompanying drawings in which, in addition to: - Figure 1 schematically illustrating the concept of universal access to multimedia content (UMA) FIGS. 2a and 2b showing the block diagrams of a perceptual frequency audio compression system, respectively to coding and decoding, FIGS. 3a and 3b schematically illustrating communication channels using transcoding. conventional and intelligent transcoding, respectively, and

FIG. 4 represents the block diagrams illustrating the conventional transcoding (upper part of the figure) and the intelligent transcoding (lower part of the figure), described above,

FIGS. 5a and 5b schematically represent the block diagrams defining the equivalence between the synthesis of the temporal signal and then the analysis with a new bank of filters (FIG. 5a) and the direct conversion between two domains of the subbands (FIG. 5b). FIG. 6 illustrates a representation in multi -addition blocks of the conventional conversion between subband domains, FIG. 7 is a multi-layer representation of the sub-domain domain conversion system, in the sense of the invention, FIG. 8 schematically summarizes the filtering method in a conversion system, within the meaning of 1'invention, Figure 9 is a representation in multiple blocks of the conversion system in the sense of the invention, in the particular case where M = pL, - FIG. 10 illustrates the filtering method in the conversion system in the sense of the invention, in the particular case where M = pL, FIG. 11 is a representation in multicast blocks of the conversion system within the meaning of the invention, in the particular case where L- = pM,

FIG. 12 illustrates the filtering method in the conversion system in the particular case where L = pM, FIG. 13 is a representation of the conversion system in the case L = pM as an LPTV system, with an input rate different from the output rate, FIG. 14 is a representation of the conversion system in the case M≈ pL as an LPTV system, with an input rate different from the output rate,

FIG. 15 is a representation of the conversion system within the meaning of the invention, as an LPTV system, in the general case where M and L are not linked by a particular relationship of proportionality,

FIG. 16 illustrates an implementation of the conversion system within the meaning of the invention by a transformation and a recovery addition operation (called OLA for "Overlap and Add") in the case where N = 3, - the FIG. 17 illustrates the conversion system within the meaning of the invention in an embodiment corresponding to an OLA recovery transform and addition for efficient implementation allowing on-the-fly processing, FIG. 18 illustrates the conversion system. within the meaning of the invention in an embodiment corresponding to an OLA recovery transform and addition for an efficient implementation allowing on-the-fly processing, in the particular case MPL, FIG. conversion in the sense of the invention in an embodiment corresponding to a transformation and an addition with OLA overlay for efficient implementation allowing on-the-fly processing, in the case by Particularly, FIG. 20a and 20b respectively illustrate a combination filtering with a conversion between domains of FIG. sub-bands, and an equivalent overall system, within the meaning of the invention,

FIGS. 21a and 21b illustrate the combination of a sampling frequency change (or "resampling") with a conversion between subband domains, conventional and in the sense of the invention, respectively, FIG. is a representation in multiple-frame blocks of the conversion system within the meaning of the invention between subband domains combined with re-sampling, FIG. 23 represents the system within the meaning of the invention as an LPTV system applied to a combined conversion with a re-sampling, FIG. 24 represents a preferred embodiment corresponding to an OLA recovery transform and addition for efficient implementation allowing on-the-fly processing of the conversion system of FIG. 23, FIG. 25 represents a transcoding occurring in a gateway GW of a communication network, for a possible application of the present invention, FIG. feel transcoding into directly with a server SER, and - 27 is a table showing the parameters of the conversion system within the meaning of the invention for particular cases of encoding formats.

The method of converting between subband domains is described below in a general discussion of the invention. The L-band synthesis bench used by a first compression coding system and defined by its filters, denoted by F ^. (Z), O≤k≤LX, and the M band analysis filter bank are considered. used in a second compression system and defined by its filters, noted

H _M (z), O≤w≤M-1. The two banks of filters used in the two compression systems are supposed to be preferentially at maximum decimation (or "critical sampling"), as will be seen below.

We denote X (z) = [X ₀ (z) X ₁ (*) ... X _W (*)] ^T and

, the signal vectors of the subbands representing the signal respectively in the areas of the first and second bank of filters.

The principle of conversion between domains of the subbands is illustrated by Figures 5a and 5b. It is a question of finding a conversion system 51 (FIG. 5b) between the vectors of the subband signals, X (λ) and Y (λ), equivalent to a cascading of the synthesis bench BS1 and the bank of BA2 analysis (FIG. 5a). The objective is to merge certain mathematical calculation operations between these two banks of filters to reduce the algorithmic complexity (that is to say the number of calculation operations and the required memory). Another objective is therefore to minimize the algorithmic delay introduced by this transformation.

By using multi-layer blocks, the diagram of FIG. 5a can be represented by that of FIG. 6, on which an analysis filter bank follows a synthesis filter bank. The synthesis filter bank subbands Z is conventionally compound in each subband k _r O≤k≤Li, an upsampling operation by ^"a factor L followed by a filtering synthesis filter The subband signal corresponding to the kth component of the input vector X (z) is therefore first oversampled and then filtered by the filter F ₁ ^ z). X (z), synthesized at the output of this synthesis bank is then obtained by summing the results of these filterings for Q≤k≤Ll.

This time signal then constitutes the input of the analysis bank to M subbands. It undergoes on each sub-band n, 0≤n≤Ml, a filtering by the analysis filter, H _M (z), followed by a subsampling operation of factor M. It then obtains at the output of this bench analysis a vector of sub-band signals, size M, shown in the domain of the z-transform Y ^(z) • ^synthesis of a time signal is therefore generally necessary in this conventional conversion system, unlike to the conversion system within the meaning of the invention which is described below.

We now describe the conversion system in the sense of the invention, according to a general expression.

We denote K the smallest common multiple of M and Z (ie K = ppcm (M, L)) and p _x and p ₂ the natural numbers such that: K = P ₁ M and K = p ₂ L. (1)

We consider X _{H H} (z)] ^τ the vector resulting from the decomposition of the vector of the signals, X (z), into p ₂ polyphase components, and

the vector resulting from the decomposition of the signal vector, Y (z), into p _x polyphase components.

Note g (z) the size matrix MxL grouping the products between the synthesis and analysis filters. The elements of this matrix are written as follows:

G _nt (z) = H _n (z) F _t (z), O »JI / -l, O≤Jfc≤Zl. (2) and, in matrix form: g (z) = h (z) f ^τ (z), (3)

respectively the vector of the analysis filters of the second bank of filters, and the vector of the synthesis filters of the first bank of filters.

The conversion between subband domains is given by the following formula:

V (z) = T (z) U (z) (4)

The conversion matrix T (z) is of size KxK. Its expression is given by: (5) where v (z) is the matrix of size p _λ xp ₂ whose elements are defined as follows:

The operation ® designates the Kronecker product such as:

Recall that the operation ^ K denotes the decimation by a factor K, corresponding to a subsampling where only one sample is selected from K samples.

The conversion system can be schematized as shown in FIG. 7, which shows that the system is advantageously a so-called "linear periodically variable time" (LPTV) system, as will be seen later.

In FIG. 7, the input block 71 consisting of the advance ^{P2 ~ x} and the delay chain, followed by the decimation 72_p ₂ -l to 72_0 by a factor p ₂ , can be interpreted as a mechanism of blocking each succession of p ₂ input vectors, denoted by X ["], into a single vector U [fc], of size K. This latter vector U [A:] is then applied to the filtering matrix T (z) (module 74) and the result is a vector V [A:], of the same size as the vector U [A:]. It is recalled that the notation X ()) simply relates to the expression of the vector X according to its transform in z, while the notation X ["] relates to the expression of the vector X in the time domain, conventionally for the skilled person.

The last block 73_pi-1 to 73_0 of FIG. 7 finally makes it possible to put in series the successive p _{ sub-vectors, each of size M, of the vector V [A:] to have as output the vectors Y [V].

The input and output blocks of FIG. 7 are finally little different from the blocking mechanisms 81 and then series-linking mechanisms 82, respectively, of FIG. 8 which summarizes the main steps of the method within the meaning of the invention.

Advantageously, the conversion system within the meaning of the invention is minimal delay.

Indeed, one of the objectives of the conversion system between subband domain is to minimize the algorithmic delay introduced. We must therefore introduce advances to reduce the delay. If we add: - an advance / delay z ^a , αeZ, at the input of the synthesis filter bank,

and an advance / delay z ^b , beZ, between the two banks of filters, then the preceding formula (5) becomes:

The exponent e _y ≈aL + b + ζiM-jL), Q≤i≤p _λ -l, 0≤j≤p ₂ -l, varies between the following two extreme values: e _raln = aL + b ~ (p ₂ -l) L = aL + bK + L, for / = 0, J = P ₂ - ^ r (9)

^{and e} _max = aL + b + (p _ι-1 ) M≈aL + b + KM, for i≈p _x -l, j = 0. (10)

The element filters of the matrix T (z), are all causal if and only if: e _mm ≤K- \, - (11)

either: aL + b≤M-1. (12)

Conversion systems within the meaning of the invention can therefore be constructed with different delays and by making different choices on the parameters a and b, but provided that the inequality (12) is preferentially satisfied.

The parameters a and b can therefore be seen as setting parameters for acting on the algorithmic delay introduced by the conversion system between subband domains.

For a minimum algorithmic conversion system, the maximum advance must be entered. The choice of a and b is therefore preferentially made so that: e _^ ≈Kl, (13)

let: aL + b = Ml. (14) For this choice, the formula (8) becomes:

or :

where, here, v (z) is the matrix whose elements are defined as follows: (17)

The relation (16) is therefore the general formula of the conversion matrix T (z), which makes it possible to minimize the algorithmic delay introduced by the conversion system within the meaning of the invention.

In the following, we will place in the context of a minimal delay conversion system.

If we use the notation e _y = M-1 + (iM-jL), with O≤ / ≤P _j -1 and 0≤j≤p ₂ -l, then the following interpretation

matrix elements Z ^ g (ZH of the matrix T (z) can be given from the formula (15):

(18)

It will be noted that the polyphase components considered in relation (18) correspond to a type decomposition 1 to the order K ₁ as described for example in the aforementioned reference:

"Multirate Systems and Filter Banks", P. Vaidyanathan, Prentice Hall, Englewood Cliffs, NJ, 1993.

This interpretation makes it possible to construct the matrix

T (z), directly from the polyphase components of type 1 to the order K of the product filters G _nk (z) ≈B. _n (z) F _k (z)

{O≤n≤M-1 and Q≤k≤L-1) and corresponding filters constructed by adding delays.

To express more explicitly the elements of the matrix T (z), we note:

The filters elements of. the matrix T (_?) can be written as follows:

for 0≤m, l≤Kl.

In this last formula (20), the integers i, n and j, k depend on / and m as follows: m and n = m-iM (21)

^~ M

where denotes the integer part of the real number x. The notation G ^r _nk (z) (with O≤r≤Kl) indicates the polyphase component number r of the filter G _nk (z), resulting from a decomposition of type 1 to the order K.

The polyphase components G ^r _{n! C} (z) (with Q≤r≤Kl) can be determined directly if the synthesis filters and the analysis filters have finite impulse responses (or "FIR"). In the case where one or both banks of filters use recursive filters (with infinite impulse responses or ¹¹ IIR "), the produced filters G _nt (z) are also infinite impulse responses. The general procedure for such a decomposition is given in Annex A, "Polyphase decomposition of recursive filters", reference:

"Audio signal processing in the coded field of techniques and applications", A. Benjelloun Touimi, doctoral dissertation of the National School of Telecommunications of Paris, May 2001.

A solution within the meaning of the invention is indicated below for the particular case where M = pL.

In the case where M = pL, it happens that K = τppcm [M, L) = M and while p ₂ ^≈ p. The formula (4) then becomes:

Y (z) = T (z) U (z). (23)

or is the vector of the polyphase components of order p of the vector of the signals X (z). The conversion matrix in this case is of size MxM and is written as follows:

(24) This matrix is therefore the line vector consisting respectively of polyphase components of general index (pk) L1 (where O≤k≤pl), following a type 1 decomposition to order M, of the matrix g (z ), synthesis filter products and analysis.

More explicitly, the element filters of the matrix T (z), write as follows:

where j and k are integers that are obtained from / by relations: •

⁽²⁶⁾

The notation G ^r _mJ (z) (with O≤r≤M-1) refers to the polyphase component of general index r of the filter G _mJ (z), resulting from a decomposition to the order M.

The schema of the conversion system is given in this particular case in FIG. 9 in multi-frame representation and in FIG. 10 illustrating the main steps of the filtering method.

The following is a solution within the meaning of the invention for the particular case where L = pM. In this particular case, it happens that K = τpτpcm (M, L) ≈L, and . Formula (4) then becomes: ^•

V (z) = T (z) X (z), (27)

or is the vector of the polyphase components of order p of the vector of the signals Y (z).

The conversion matrix in this case is of size LxL and is written as follows:

This matrix is therefore the column vector consisting respectively of polyphase components of general index (k + 1) M1 (with O≤k≤p-1), following a type 1 decomposition at order L, of the matrix g ( z), synthesis filter products and analysis.

More explicitly, the element filters of the matrix T (z), write as follows:

(29) where / and k are integers that are obtained from m by: mk = and i ≈ m ~ kM (30)

^~ M

The notation G ^r _tl (z) (with O≤r≤X-1) indicates the polyphase component of general index r of the filter G ^ z), resulting from a decomposition to the order L.

A possible choice for parameters a and b is to take α = 0 and b≈M-1. Other choices may be provided provided that the equality (14) is preferentially satisfied to result in a minimal delay system.

The diagram of the conversion system is given in this case in FIG. 11 in multi-layer representation and in FIG. 12 illustrating the main steps of the filtering method in this particular case where L≈pM.

The conversion system within the meaning of the invention is now described according to the aspect of a periodically varying linear system. In this case, it is indicated that the filters of the synthesis and analysis banks are preferentially critical sampling.

The diagram of the conversion system given in FIG. 7 shows that the latter is a linear system that varies periodically or "LPTV (for Linear Periodically Time Varying"), in the sense of the reference:

"Multirate Systems and Filter Banks", PP Vaidyanathan, Prentice Hall, Englewood Cliffs, NJ, 1993, in section 10.1. To determine the period of this system and find its equivalent structure which illustrates this property, we first expose the particular cases L = pM and M = pL below.

Signal sample we denote by f _s frequency in the time domain, and f _Sι f and _h the sampling frequencies in the areas of the first and second filter bank, respectively. We also note T ₁ , r _Si and T _h respectively the corresponding sampling periods. These settings verify the following relationships:

In the particular case where L≈pM, taking into account the scheme of Figure 7 and the formula (28) of the conversion matrix, it can be deduced that the conversion system is linear periodically varying in time with a period pT _H = T _S. It can be represented by the structure of FIG. 13. It is characterized by the set of p transfer matrices A ₄ (z) (with O≤k≤p-1) defined by:

This system does not have the same flow in and out. The input rate is f _s and the output rate is f _s = pf. Transfer matrices A. _k (z) operate at the sampling frequency f and the overall system functions as if a switch 130 (FIG. 13), at the output of the system, was also circularly swung to the same frequency f _Sχ of an output of a matrix block A _k (z ) to the other.

It will also be noted that the output of the system Y ["] _/ at the instant nT _s , is equal to the output of the matrix A ₄ (z), to

the moment p

In the other particular case where M = pL, taking into account formula (24) of the conversion matrix applied in this case, the diagram of FIG. 7 becomes that of FIG. 14.

This conversion system can be seen as a system

LPTV of period pT _Si = T _S2 , characterized by the set of p matrices A ₄ (Z) (with O≤k≤pl) defined by the relation

(33) and followed by a summation on all their outputs, with:

(33)

The input rate of this system is f -pf _s and the output rate is f ^. The transfer matrices A _k (z) operate at the sampling frequency / et and the system operates globally as if a switch 140 (FIG. 14), at the input of the system, was flipping in a circular manner to this same frequency f _s , from one input of a matrix block A _A (z) to the other.

It is further indicated that the output of the conversion system Y [ ^w ] 'at the instant nT _Si , is equal to the sum of the outputs of the \ { ^z ) (with O≤k≤p-1), each fed by, at the respective moments:

The operation of the system is now described in the general case where M and L are not necessarily linked by a proportionality relation. Taking into account the shape of the matrix T (z) given by relation (15), the diagram of FIG. 7 and the explanations given above for the two particular cases L = pM and M = pL, the conversion system in the general case can be schematized as shown in Figure 15. The general system comprises P ₁ periodically varying linear subsystems, each of period P ₂ T ^. The LPTV subsystem of order / (with O≤ / ≤ ^ _j -1), from this set, is characterized by the following p ₂ transfer matrices A _y (z):

All of these subsystems operate in parallel and one of their outputs is selected periodically as the output of the system with a period p _λ T _Si . The overall system is also linear periodically varying in time period KT ₅ . Indeed : (35)

therefore (36)

The two switches 151 and 152 shown respectively at the input and the output of the structure of FIG. 15 operate with a frequency - which is also

K the operating frequency of the transfer matrices A _u (z).

The output of the system Y [n], at the instant nT ^, is equal to the output of the subsystem LPTV number i, at the instant nT _Si , where i = n mod /? _! . The input of the system X [A:], at the instant kT ^, is directed to the number entries j of each of the p _x subsystem LPTV, where j = kmoάp ₂ .

The input rate of this system is / ^ and the output rate is f _s , allowing processing of the input data, on the fly, by the conversion system within the meaning of the invention.

We recall that the expressions of the filters A _{/ y> t} (z) (where

O≤n≤Ml and O≤k≤Ll), elements of a transfer matrix A ^ z), depend on e _tJ , thus indices / and j, and are written as follows:

and if «, <0. (38) An advantageous implementation of the conversion system in the sense of the invention is described below.

We will denote by TV ₁ the length of the filters F _t (z) (where O≤k≤Ll), and N ₂ the length of the filters H _n (z) (where O≤w≤Z-1). These notations are used only in the case where these filters have finite impulse responses and the same length for each of the two banks of filters.

The following writes of the input and output vectors of the matrix filter block are used by T (z):

(39)

and (40)

An implementation based on matrix filtering results directly from the formula (4) and the representative diagram of the conversion system of the general figure 8. Thus, each signal V _m [&], with 0≤m≤Kl, component of vector V [Al ^'is ^ ^{a sornme} the results of filtering each of the signals U, [&] with Q≤l≤K-1, by the filter T _{ra /} (z).

In the case of synthesis filter banks and finite impulse response analysis, all element filters of the matrix T (z) will also be finite impulse response filters. Conventionally, it is possible in this case to use fast methods of filtering based on convolution-multiplication properties. In the case of filters with infinite impulse responses, it is indicated that it is possible to factor certain denominators between the elements of the matrix

T (z) during the implementation.

An implementation using a recovery transform is now described. It is assumed here that the filters of the synthesis and analysis benches have finite impulse responses and maximum decimation.

The conversion matrix T (z) is expressed as follows:

where the P _n are matrices of size KxK, and N corresponds to the maximum of the lengths of the filters T _{ffl /} (z), elements of T (z).

This length JV, in the most general case, is given by the following expression:

if r ₀ ≥ M + L and M and L are not multiples of each other,

, if not,

(42) where r ₀ is given by

. : 43) In the following, we use the following definition of length N:

taking into account the variations according to the cases.

The filtering operation by the matrix T (z) can then be written as follows:

Consider the matrix P, of size NKxK, defined by:

The system can therefore be constructed by a matrix transform P, followed by a recovery addition operation. This implementation is similar to the synthesis part of an overlapping transform "LT" (for "Lapped Transform"), as described in particular in: "Signal Processing with Lapped Transform", HS Malvar, Artech House, Inc. 1992 .

It is represented in FIG. 16 for the particular case where N = 3. The matrix P will be called "converted conversion matrix".

The calculation procedure for conversion between subband domains can then be summarized as follows:

1. Construction of a vector U [«] from p ₂ successive vectors at the input of the conversion system and corresponding to the vectors of the signals of the subbands X [£] of the first bank of filters.

2. Transformation of the vector U ["] by the converted transformation matrix P to obtain the vector W [n]:

W [ «] = PU ["]. (47;

3. Addition operation with overlap on N successive vectors W ["- iV + 1], ..., W [nl] and W ["] as illustrated in FIG. 16. The output of this operation is the vector V [«]. 4. Serialization of the successive sub-vectors, of sizes M, of the vector V ["] to obtain the vectors of the subband signals Y [r] of the domain of the second bank of filters.

An implementation based on the representation of the system as an LPTV system according to a preferred embodiment is described below.

The method presented below provides a parallelism in the treatment and efficient use of IT resources (-logi-cial-matéxiisΗre or ^~ s) for the implementation of the process. It is therefore a presently preferred embodiment at least in the case of finite impulse response filter banks.

We consider the matrices B _y (with O≤i≤p ^ -1 and O≤j≤P ₂ -I), of size NMxL, as the transformed matrices associated with each of the transfer matrices A _y (z) defined below. before. If we express these matrices by where the matrices B _IJn are of size MxL, then the matrix B _tJ can be defined as follows:

Since each transfer matrix A ,, (z) contains filters of identical lengths and which depend on the value of e _ij , then the corresponding matrix B _(J) also depends on e _ij.The matrices B _/ contain zero sub-matrices. and their forms are given as follows: o If 0 <e _ij <r ₀ -l then:

^B y, w-2 ⁰ LxM J ^• ( ⁴⁹ )

o If r _o ≤e _ij ≤K - 1 then:

⁽ 50 ⁾

• For e _ij <0,

o If 0≤K + e _ij ≤r ₀ -l then:

⁽ 51 ⁾

Note that this case only exists if K + e _mia ≤r ₀ -1. Now, e _min = M + LK, so that the existence condition of this case is such that r _o ≥M + L. o If r ₀ ≤K + e _ij ≤Kl then:

(52) Remember that 0 _LxM denotes the zero matrix of size LxM.

Advantageously, the null blocks of the matrices B _{/ y} allow a reduction of calculation during a transformation of an input vector by this matrix.

Note the following relation between the submatrices P _n of P and the submatrices B _n :

(53)

The calculation procedure for conversion between subband domains is illustrated in FIG. 17 and is conducted as follows: 1. Each new input vector X [&] is oriented towards a common memory of the subsystems characterized by the matrices transformed B _y , where 0≤ / </?, - 1, such that j = kmoάp ₂ .

2. For, each / fixed where O≤i≤p ^ -1, a. For j = kmoάp ₂ , application of the transform B ^ to the vector X [&] • During this transformation, the null blocks of the matrix B _tj are advantageously taken into account. b. Summation of all transformed vectors resulting from step 2.a, for j = 0, ..., p ₂ -l. vs. Addition with overlay "OLA" (for "OverLapp and Add") on the sum vectors resulting from step 2.b to build the output Y, ["] of the subsystem LPTV number /. 3. The output Y ["] of the conversion system corresponds to the output Y _/ ["] of the LPTV subsystem number / such that i = n mod ^.

Addition with cover 2.c step is done on vectors ^• NM length with a covering (NI) M elements.

Note that this procedure is always based on the scheme of Figure 15.

In the particular case M = pL, we express with O≤j≤p-1, and B B denotes the corresponding transformed matrix. This matrix has the following form:

or

The calculation steps for the conversion between subband domains, as shown in Figure 18, are as follows:

1. Each new input vector X [k] is directed to a memory of the subsystem characterized by the transformed matrix B _y , such that j = kmodp.

2. For j = kmoάp, apply transform B. to vector X [A:]. 3. summation of the vectors resulting from step 2, out of the subsystems characterized by the transformed matrices B _; , for O≤j≤pl.

4. The output Y ["] of the conversion system corresponds to the result of the overlap addition on the sum vectors resulting from step 3.

We write, in the particular case where L = pM:

and B is the corresponding transformed matrix. This matrix has the following form:

^(55;

OR

The calculation steps for the conversion between subband domains are illustrated in FIG. 19 and are preferably carried out as follows:

1. Each new input vector X [&] is oriented to the common memory of all the subsystems characterized by the transfer matrices A,. (Z), with 0≤i≤p-1.

2. For each / fixed, such that 0≤i≤pl, application of the transform B. to the vector X [^] then addition with overlap to obtain the vector Y ,, ["]. 3. The output Y ["] of the conversion system then corresponds to the output Y, ["] of the subsystem characterized by the transfer matrix A, (z) such that i≈n modp.

Hereinafter, the most used filterbanks are described in audio coding. It is also indicated that the parameters of the conversion system for different cases of switching between filter banks using such encoding formats are given in FIG. 27, where the parameter N is given by the formula (56) above.

For a conversion between banks of modulated cosine FIR filters, the filter bank is characterized by the fact that the analysis and synthesis filters are obtained by a cosine modulation of a low-pass protector filter.

H (z). For an M band filter bank, the expression of the impulse responses of the analysis and synthesis filters is given in:

with O≤M≤.V-1 and where h [n] is the answer impulse of the prototype filter, of length N.

This type of filter bank has the property of perfect reconstruction if in addition the following conditions are verified: the length of the filters is given by N = ImM, where m is an integer,

the synthesis filters are given by / _A [n] = Λ _A [iV-l- "],

the prototype filter is linear phase / z []] = Λ [iV-1-]], and the polyphase components of order 2M of the prototype filter H (z) further satisfy the condition of complementarity in power, which allows to design the prototype filter.

Equations (57), (58) and the above conditions make it possible to fully characterize a modulated cosine filter bank with perfect reconstruction.

These modulated cosine filter banks with perfect reconstruction are the basis of all the filter banks of the current audio coders. Even the pseudo-QMF filter bank of the MPEG-1/2 layer I & II coders can be associated with this category, it being understood that the prototype filter is sufficiently well designed to consider that the perfect reconstruction is satisfied.

For conversions between MDCT transforms of different sizes, constituting a particular case of modulated cosine filter banks and perfect reconstruction, an example may be the TDAC filter bank for which N = IM and m = 1. The latter can be considered as an MLT transform (for "Modulated Lapped Transform") also known as MDCT (for "Modified DCT"). This transform is used in most coders current frequency audio (MPEG-2/4 AAC, PAC, MSAudio, TDAC, etc.).

The expressions of the synthesis and analysis filter banks are given by:

(59) and h _k [n] = f _k [2M - \ - n]. (60)

To ensure perfect reconstruction, the window must check the condition of symmetry: and complementarity in power: .

A possible and simple choice ^'for the prototype filter satisfying these conditions is given by the following sinusoidal window:

This window choice is used in TDAC and G.722.1 encoders. Another choice is to take a window derived from the Kaiser-Bessel window (or "KBD") as in the case of MPEG-4 AAC, BSAC, Twin VQ and AC-3 encoders.

It will be understood that formulas (59) and (60) and the choice of the window thus completely define the filter bank corresponding to the MDCT transform. As regards a conversion between the MPEG-I PQMF filter bank and an MDCT, it is indicated that the filter bank in the MPEG-1/2 Layer I & II coder is a pseudo-QMF with M = 32 bands. These analysis and synthesis filters are defined as follows:

for 0 <A <31 and 0 <<511.

The coefficients h [n] of the impulse response of the prototype filter can be found in: - "Introduction to Digital Audio and Standards", M. Bosi, R. E. Goldberg, pp 92-93, Kluwer Academy Publishers (2002).

The values provided in the MPEG-I Audio Layer I-II standard correspond to the window (-1) h (2lM + j), with 0 <j≤2M ~ l and 0≤ / <m-1.

An aspect of the invention is described below in which the conversion between subband domains would be combined with a filtering process.

During a transcoding operation, it is possible to perform an intermediate processing on the decoded signal before recoding it in the new format. Several multimedia signal processing (audio, image and video) are based on linear filtering. Examples are: • Image or video filtering for resampling (switching from CIF format to QCIF).

• Audio filtering by HRTF filters ("Head Related Trasfert Functions") for sound spatialization. This is one of the interesting cases of combination of transcoding and spatialization. One possible application would typically be the processing in teleconferencing audio bridges.

With respect to the block diagram of FIG. 5a, it is a matter of introducing a filter S (z) between the two banks of synthesis and analysis filters and of finding an equivalent system. The block diagrams are shown in FIGS. 20a and 20b.

The conversion system combined with the filtering can be modeled by the same type of scheme as that shown in FIG. 5b. However, it is characterized by the new filter matrix T (z) defined by:

(64) where g (z) is the matrix of size MxL whose elements are given by: (65)

In expression (64) above, the matrix ^v ( ^z ) corresponds to the definition of formula (17). More explicitly, the formula (64) is written as follows:

(66) We now describe a conversion between subband domains combined with a change in sampling frequency.

We consider here the case where a change of sampling frequency is performed on the synthesized time signal before being re-analyzed by the second analysis bench. The system within the meaning of the invention therefore combines the conversion between subband domains and the change in sampling frequency, as illustrated in FIGS. 21a and 21b.

In Figure 21a, we consider a sampling frequency change system by a rational factor

-, or. Q and R are natural numbers supposed to be first R between them, so such that gcd (£ λ, i?) = 1, without loss of generality.

In this system, the filter S _FB (z) is a low pass filter of standardized cutoff frequency and gain in bandwidth Q.

We define here K 'as the least common multiple of QL and RM (K' = ppcm (QL, RM)) and q _ιf q ₂ the two natural _numbers such that:

K '= q _x RM and K' = q ₂ QL. (67)

Note that q _λ and q ₂ are prime between them.

We consider in this case the vector

X £ _, (z)] resulting from the decomposition of the vector of the signals X (z) in q ₂ polyphase components,

and the vector resulting from the

decomposition of the vector of the signals Y ( ^z ) into q _x polyphase components.

The conversion system combined with the sampling rate change can be modeled by the scheme of Figure 22. It is characterized by the filter matrix T (z) of size q _x Mx.q ₂ L, defined as follows:

where g (z) is the matrix of size MxL whose elements are given by: (69) and v (z) is the matrix whose elements are defined as follows: (70) also respecting the following relation: (71)

According to formula (69), G _nk [z) is interpreted as the result of the convolution of the filter H _n (z) oversampled by a factor R, the filter S _Pβ (z) and the filter F ₄ (z ) oversampled by a Q factor. To reduce the delay of the overall system, it is possible to choose the matrix v (z) whose elements are defined as follows: _{(7 2)} or

The same interpretation can be given to the formulation of the matrix T (^) as that given above. Thus, the filters T _{m /} (z), with O ≤ m ≤ q _x M -1 and Q ≤ l ≤ q ₂ L - \, elements of this matrix, can be written as follows:

for O≤w≤ ^ M-1 and 0≤l≤q ₂ Ll, and where e ^ ≈c _^ + iRM-jQL. The integers /, n and j, k are obtained directly from / and from:

(74 ^'

(75;

The same developments and explanations given for the system of conversion between subband domains remain valid for this new combined system by replacing the matrix T (z) by T (z) and taking into account the parameters that characterize it. The system still presents itself as a periodically varying linear system over time (LPTV). The preferred implementation method described above and the simplification of the system in particular cases can be provided as well. in this application. It should be noted, however, that the particular cases to be distinguished in the present system relate to the case where RM and QL are multiples of one another.

In this case, the system according to FIG. 23 operates with the matrices A _{/ y} (2) such that:

. (76)

In the case of an implementation using a recovery transform, preferably on the assumption that the banks of synthesis and analysis filters, as well as the low-pass filter used in resampling, are finite impulse responses , so that :

where the matrices B ₀₁₁ are of size MxL, the following definition of matrices B 1 as shown in FIG. 24 can be given as follows:

In general, it will be understood that the present invention provides a generic solution for converting a representation of a signal from one subband (or transform) domain to another. The method is preferably applied in the context where the banks of filters used by the two compression systems are maximum decimation, as has been seen above. Although the above detailed description is essentially concerned with audio coding, the described embodiments may be provided for all transform or subband coders of multimedia signals, especially those used in video, picture, speech coding, or other. These embodiments can also be implemented in any device having a cascade of a synthesis bench and an analysis bench, in particular in the following examples: • Improvement of the quality of the speech in sub-bands followed echo cancellation in sub-bands and vice versa.

• Echo cancellation or sub-band noise suppression algorithm followed by a subband encoder.

• Subband decoder followed by echo cancellation or subband suppression algorithm

• Method of reconstruction of the high frequency band in audio by a method such as SBR (for "Spectral Band Replication") because this method implements an analysis bench and has for input the output of an audio decoder.

It will thus be understood that the application of the invention is not limited to a simple transcoding between two different coding formats.

Nevertheless, hereinafter, some applications are described with regard to audio transcoding. Transcoding between audio encoding formats is becoming increasingly important given the current diversity of existing terminals and transport and access networks. '-

Depending on the service and the delivery scenario of the audio content, transcoding can occur at different points in the transmission chain. In the following, we distinguish some possible case.

Broadcasting refers to digital broadcast systems that use different types of audio encoders. Thus, in Europe (DVB standard), MPEG-2 BC audio Layer II encoders are indicated. In contrast, in the USA, the Dolby AC-3 encoder is recommended. In Japan, the MPEG-2 AAC encoder is chosen. The transcoding mechanism TRANS is advantageous in a gateway GW in the network RES of transmission of the audio content coming from a server SER and destined for a first terminal TER1, equipped with a decoder DECl and another terminal TER2. equipped with another decoder DEC2, as shown in Figure 25.

In so-called Streaming applications in multicast mode, a single content is preferably transmitted to several terminals TER1, TER2, for reasons of optimization of the bandwidth in the transport network RES. Personal adaptation is done at the last node of the network for each end user. These users may have terminals supporting different decoders, hence the transcoding utility in the network node, as shown in the previous figure. In the case of streaming in unicast mode, transcoding TRANS (FIG. 26) can be done with the server SER to adapt the content to the capabilities of the terminals TER1, TER2. Terminal capacity information was previously received and analyzed by the SER server.

In "download" mode, the audio content is stored in a given encoding format. It is transcoded in real time to be compatible with the terminal at every request of a user before being downloaded.

In group communication (teleconference, audio conference, or other), the terminals involved may have different capabilities in terms of coders / decoders. In a centralized teleconferencing architecture, implementing an audio bridge, transcoding can occur at the bridge.

Table 3 below now shows some possible transcoding, advantageous, between audio coding formats according to the fields of application.

Table 3: Examples of some interesting types of transcodings and their areas of application.

FIG. 27 then indicates the parameters of the conversion system within the meaning of the invention for these particular cases of coding formats.

Claims

claims

A method implemented by computer resources for processing data by passing between different subband domains, consisting in compacting in the same process the application of a first vector (X (z)) having a first number L of respective subband components, to a synthesis filter bank, and then to an analysis filter bank, to obtain a second vector (Y (z)) having a second number of components

M in respective subbands, characterized in that it comprises the following steps, after determining a third number K, the least common multiple between the first number L and the second number M: a) if the third number K is different from the first number L, set in blocks by serial / parallel conversion of the first vector to obtain p ₂ polyphase component vectors, with b) applying a chosen matrix filtering, involving a square matrix T (z) of dimensions KxK, to said p ₂ polyphase component vectors to obtain P ₁ polyphase component vectors of the second vector, c) if the third number K is different from the second number M, set in blocks by parallel / serial conversion to obtain said second vector.

2. Method according to claim 1, characterized in that the serial / parallel conversion of step a) corresponds to the application, to the first vector (X (z)), of an advance z ^{Pl ~ x} , followed by a delay chain with subsampling by a factor p ₂ , to obtain said p ₂ component polyphase vectors, corresponding to a decomposition of the order p ₂ , of the first vector (X (z)).

3. Method according to one of claims 1 and 2, characterized in that the parallel / series conversion of step c) comprises an oversampling of a factor p _λ applied to p _x component vectors polyphase, corresponding to a decomposition of the order p _x , intended to form the second vector (Y (z)).

4. Method according to one of claims 1 to 3, characterized in that said square matrix T (z) results from a decimation of a factor K applied to a matrix formed of p _: xp ₂ sub-matrix expressing each by z ^IM - ^JL g (z), where: z ^x denotes an advance or a delay, according to the sign of x,

- i is between 0 and J ^ ₁ -I,

- j is between 0 and /? ₂ -l, and - g (z) is a matrix of dimensions MxL resulting from the product h (z) .f ^τ (z), where h (z) and f (z) are the vectors of the respective transfer functions the banks of analysis and synthesis filters, the notation M ^τ denoting the transposed matrix of M.

5. Method according to claim 4, characterized in that a further advance z ^{M ~ x} is applied to all P _x XP ₁ sub-matrices, to obtain elements of said matrix T '(z) each corresponding to a causal filter and together defining a conversion system with minimal algorithmic delay.

6. Method according to claim 5, characterized in that said elements of the matrix T (z) are expressed as a function of polyphase components of the order K of product filters G _nA (z) given by G _nk (z) = H _n (z) F _λ (z), with: n between 0 and MI and k between 0 and LI, and

- H _n (z) and F ₄ (z), the n ^th and the k ^th components of the vectors of the transfer functions respectively associated with the banks of analysis and synthesis filters.

7. Method according to claim 5, in which, between the synthesis filter bank and the analysis filter bank, additional filtering is furthermore provided.

S (z), characterized in that the elements of the matrix T (z) are expressed as a function of polyphase components of the order K of product filters G _nk ( ^z ) given by G _nk (z) = H _n ( z) S (z) F _k (z), with:

n between 0 and MI and k between 0 and LI, and - H _n (z) and F ₄ (Z), the n ^th and the k ^th components of the vectors of the transfer functions respectively associated with the banks of analysis and synthesis filters.

8. Method according to one of claims 6 and 7, characterized in that the element filters T _{m /} (z) of the matrix T (z) are expressed by:

T.. with e, ≈ (Ml) + (tM-JL), and where: - in the notation G ^x _nk (z), x corresponds to a polyphase component number, resulting from a decomposition to the order K, of the product filter G _nk (z), i corresponds to the integer part of the report m / m,

- j corresponds to the integer part of the ratio 1 / L, - the number n is given by n = m-iM, and

the number k is given by k = l-jL.

9. Method according to claim 8, characterized in that, if the second number M is a multiple of the first number L, the element filters T _{m /} (z) of the matrix T (z) are expressed by T _ml (z ) = G)% 7 ^k ' ^{L ~ ι} (z), m and 1 being between 0 and MI, and where:

- p = M / L,

- k is the integer part of 1 / L, and - the number j is given by j = l-kL.

10. Process according to claim 8, characterized in that, if the first number L is a multiple of the second number M, the element filters T _{m /} (z) of the matrix T (z) are expressed by m and 1 being between 0 and LI, and where:

k is the integer part of m / M, and the number i is given by i = m-kM.

11. Method according to one of the preceding claims, characterized in that it consists in applying a linear type conversion system periodically varying in time, and period T defined by T = KT ₃ , with T _s = T ₃₁ / L = T _s2 / M, where T _s i and T ₃₂ are the respective sampling periods in the areas of the synthesis filter bank and the analysis filter bank, in critical sampling.

12. Method according to claim 11, characterized in that it consists in applying pi linear subsystems periodically varying in time, each of period P ₂ .T _s i, and in periodically selecting the outputs of the successive subsystems, with a period pi.T _S 2.

13. Method according to claim 12, characterized in that the input rate of the overall conversion system is 1 / Tgi, while its output rate is 1 / T ₃₂ , to process input data on the fly. .

14. Method according to one of claims 12 and 13, taken in combination with claim 8, characterized in that each subsystem, of index i between 0 and pi ~ 1, includes P2 transfer matrices A _y ( z), with j being between 0 and P ₂ -I, the elements of which are filters K _{l] nk} {z), with n between 0 and MI and k between 0 and LI, such that:

15. Method according to one of the preceding claims, in which the filters of the synthesis and analysis banks have finite impulse responses, characterized in that said chosen matrix filtering is expressed by a P-matrix overlap transform, dimensions NKxK and such that:

the sub-matrices being of dimensions KxK and verifying, with the matrix T (z), the relation:

where N is the maximum of the lengths of the element filters of T (z).

16. The method according to claim 15, characterized in that the maximum N of the lengths of the element filters of T (z) is given by the following expression:

or : r ₀ is given by the relation r _Q = (N _ι + N ₂ -2) modK,

- N ₁ and N ₂ are the respentive lengths of the filters of the synthesis bench and the analysis bench, the notation mod "designating the modulo of the number n, the notation denoting the integer part of the real number x.

17. Method according to one of claims 15 and 16, characterized in that it comprises the following steps, for a conversion between subband domains:

constructing a vector U [n] from P ₂ first successive vectors X [&], in the sub-band domain of the synthesis filterbank,

applying to the vector U [n] of the conversion transformed matrix P, to obtain a vector W [n] = P.U [n],

- addition with overlap on N successive vectors W [n-Ν + 1], W [n-N + 2], ..., W [n-1], W [n], to form a vector V [n] ,

- Serialization of successive sub-vectors of the vector V [n], these sub-vectors being each of dimension corresponding to the second number M, to form said second vector (Y [r]).

18. The method of claim 17, characterized in that it comprises the following steps:

applying a first vector X [k], expressed in the field of the sub-bands of the synthesis filter bank, to the subsystems comprising the transformed matrices B _& . with i between 0 and pi-1 and j such that j = kmodp ₂ , for each fixed i, ranging from 0 to pi-1:

* application of a transform, matrix B _; , to the vector

X [k] for j = kmodp ₂ , each B _{/ y} matrix being expressed as follows:

where the elements B ^ _n are such that:

For all n between

0 and N-I,

summation of all the vectors resulting from the transform for j = 0, ..., p ₂ -1, * addition with overlap on the vectors resulting from the summation, to build, at the output of subsystem of index i, a vector Y _i [n],

obtaining a vector Y [n], at the output of the global conversion system, corresponding to the vector Y, [n] of the index subsystem i such that i = n modp ₁ , the notation modn designating the modulo of the number n.

19. The method as claimed in claim 18, characterized in that the matrices B _ij comprise null blocks of dimensions LxM such that:

for 0≤e _ij ≤K-1,

. if 0≤e _ij ≤r _Q -1 then:

if r _o ≤e _IJ ≤Kl then:

for e _tJ <0,

. if 0 ≤ K + e _tJ <r _o -l then:

if r ₀ ≤ K + βy ≤ K -l then

KM] with:

* Q _LxM denoting a null block of dimensions LxM, and

N ₁ and N ₂ are the respective lengths of the filters of the synthesis bench and of the analysis bench,

the notation modn designating the modulo of the number n,

- the notation denoting the integer part of the real number x.

20. The method according to claim 19, characterized in that, if the first number M is a multiple of the second number L such that M = pL, the matrices A _tJ become

- Q≤j≤pl, - and B _j are the transform matrices that are expressed by:

or the notation denoting the integer part of the real number x.

21. The method of claim 20, characterized in that it comprises the following steps:

application of a first vector X [&], expressed in the field of the sub-bands of the synthesis filter bank, to a subsystem comprising the transformed matrix B _y with summation of the vectors resulting from the application of transformed matrices B ₇ , for all j such that O≤j≤p-1,

obtaining the vector Y ["], at the output of the overall conversion system, by addition with recovery on the vectors resulting from said summation, the notation mod" designating the modulo of the number ".

22. Method according to claim 19, characterized in that, if the second number L is a multiple of the first number M such that L = pM, the matrices A _tJ become

, or :

- 0≤i≤pl _r and

B _; . are the transform matrices that express themselves by:

where / ₀ = -2- -1, the notation | _xj denoting the integer part

the real number x.

23. The method of claim 22, characterized in that it comprises the following steps:

application of a first vector X [&], expressed in the sub-band domain of the synthesis filterbank, to a subsystem comprising the transfer matrix A, (z), with 0≤i≤pl, - for all / fixed such that O≤i≤pl, application of a transform, of matrix B, to the vector X [A:], and addition with overlap to obtain an output vector Y, [«],

obtaining an output vector Y ["] _/ of the global conversion system, corresponding to the vector Y, ["], with i such that i = n moàp, the notation mod / i denoting the modulo of the number n.

24. The method as claimed in one of claims 4 to 23, in which the filters of the analysis and synthesis banks are of the modulated cosine and finite impulse response type, characterized in that the analysis and / or synthesis are obtained by a cosine modulation of a low-pass prototype filter H (z), so that the impulse responses of the analysis and / or synthesis filters, forming the vectors of the transfer functions h (z) and / or f (z), respectively, each expresses, for a bank of filters with M bands, by:

or

_

- is the impulse response of the prototype filter, of length N,

- n is such that O ≤ n ≤ N-1.

25. The method of claim 24, characterized in that:

the length JV of the filters is given by N = 2 mM, where m is an integer, the synthesis filters are given by

- The prototype filter is linear phase and verifies the relation / z [w] = / z [JV-l-w], and the polyphase components of order 2M of the prototype filter H (z) satisfy a condition of complementarity in power.

26. The method according to claim 25, characterized in that N = 2M and the expressions of the synthesis and analysis filter banks are given by:

for O≤k≤M-1, 0≤n≤2M- \,

and in that the impulse response of the prototype filter h [n] further satisfies the following conditions: - h [l] = h [2M-11], and

- λ ² [/] + Λ ² [/ + Λ_f] = 1, for / between 0 and 2M-1.

27. The method of claim 26, characterized in that the impulse response of the prototype filter is given by the relation:

for 0 ≤n ≤ 2M-1.

28. The method of claim 27, wherein the synthesis filter bank is in a pseudo-QMF type format, M = 32 bands, and the analysis filter bank is MDCT type, or conversely, characterized in that the analysis and synthesis filters are respectively defined by:

for 0≤ &<31 and 0 <ra <511

29. The method according to claims 4 and 5, characterized in that, if it is further provided a resampling of a Q / R rational factor between the synthesis filter bank and the analysis filter bank, the filter matrix T (-z), of size q _λ Mxq ₂ L, is defined by: or :

- is the matrix of size MxL whose elements are given by:

is the matrix whose elements are preferentially defined by:

with and S _PB (z) is preferably a low-pass filter of cutoff frequency and gain in bandwidth Q.

30. Application of the method according to one of the preceding claims to the transcoding of a first type of coding / decoding in compression to at least a second type of coding / decoding in compression, characterized in that it consists in compacting in the same processing the following steps: recovering data at least partially decoded according to said first type, in the form of a first vector (X (z)) having a first number L of components in respective subbands,

applying the first vector to a synthesis filter bank according to the first type, then to an analysis filter bank according to the second type, and

recovering a second vector (Y (z)) having a second number of components M in respective subbands and may be applied to subsequent coding steps according to the second type.

31. Computer program product, intended to be stored in a memory of a device in a communication network, such as a server, a gateway, or a terminal, characterized in that it comprises instructions for the implementation of of all or part of the method according to one of claims 1 to 29.

32. Equipment such as a server, a gateway, or a terminal, intended for a communication network, characterized in that it comprises computer resources for the implementation of the method according to one of claims 1 to 29. .