EP2034473A2 - Dispositif et procédé destinés à déterminer une valeur d'évaluation - Google Patents

Dispositif et procédé destinés à déterminer une valeur d'évaluation Download PDF

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Publication number
EP2034473A2
EP2034473A2 EP08021083A EP08021083A EP2034473A2 EP 2034473 A2 EP2034473 A2 EP 2034473A2 EP 08021083 A EP08021083 A EP 08021083A EP 08021083 A EP08021083 A EP 08021083A EP 2034473 A2 EP2034473 A2 EP 2034473A2
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Prior art keywords
energy
measure
signal
band
distribution
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EP08021083A
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German (de)
English (en)
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EP2034473B1 (fr
EP2034473A3 (fr
Inventor
Michael Schug
Johannes Hilpert
Stefan Geyersberger
Max Neuendorf
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Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV
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Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV
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Priority to PL08021083T priority Critical patent/PL2034473T3/pl
Priority to PL19167397T priority patent/PL3544003T3/pl
Priority to EP19167397.9A priority patent/EP3544003B1/fr
Publication of EP2034473A2 publication Critical patent/EP2034473A2/fr
Publication of EP2034473A3 publication Critical patent/EP2034473A3/fr
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/002—Dynamic bit allocation
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • G10L19/022—Blocking, i.e. grouping of samples in time; Choice of analysis windows; Overlap factoring
    • G10L19/025—Detection of transients or attacks for time/frequency resolution switching
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters

Definitions

  • the present invention relates to encoders for encoding a signal comprising audio and / or video information, and more particularly to estimating a need for information units to encode that signal.
  • an audio signal to be coded is fed. This is first supplied to a scaling stage 1002 in which a so-called AAC gain control is performed to set the level of the audio signal. Scaling page information is provided to a bitstream formatter 1004, as indicated by the arrow between block 1002 and block 1004. The scaled audio signal is then applied to an MDCT filter bank 1006.
  • the filter bank implements a modified discrete cosine transform with 50% overlapping windows, the window length being determined by a block 1008.
  • block 1008 is for windowing transient signals with shorter windows, and for windowing stationary signals with longer windows. This serves to achieve a higher time resolution (at the expense of frequency resolution) due to the shorter transient signal windows, while for more stationary signals, higher frequency resolution (at the expense of time resolution) is achieved by longer windows is achieved, with longer windows tend to be preferred because they promise a larger Codier stand.
  • temporally successive blocks of spectral values are present, which, depending on the embodiment of the filter bank, may be MDCT coefficients, Fourier coefficients or even subband signals, each subband signal having a certain limited bandwidth passing through the corresponding subband channel in the filter bank 1006, and wherein each subband signal has a certain number of subband samples.
  • the filter bank outputs temporally successive blocks of MDCT spectral coefficients, which generally represent successive short-term spectra of the audio signal to be encoded at input 1000.
  • a block of MDCT spectral values is then fed to a TNS processing block 1010 where temporal noise shaping (TNS) takes place.
  • TNS temporal noise shaping
  • the TNS technique is used to shape the temporal shape of the quantization noise within each window of the transform. This is achieved by applying a filtering process to parts of the spectral data of each channel.
  • the coding is performed on a window basis. In particular, the following steps are performed to apply the TNS tool to a window of spectral data, that is, to a block of spectral values.
  • a frequency range is selected for the TNS tool.
  • a suitable choice is to cover a frequency range of 1.5 kHz up to the highest possible scale factor band with a filter. It should be noted that this frequency range of the sampling rate depends as specified in the AAC standard (ISO / IEC 14496-3: 2001 (E)).
  • LPC linear predictive coding
  • the expected prediction gain PG is obtained. Further, the reflection coefficients or Parcor coefficients are obtained.
  • the TNS tool is not applied. In this case, control information is written in the bit stream for a decoder to know that no TNS processing has been performed.
  • TNS processing is applied.
  • the reflection coefficients are quantized.
  • the order of the noise shaping filter used is determined by removing all the reflection coefficients having an absolute value less than a threshold from the "tail" of the reflection coefficient array.
  • the number of remaining reflection coefficients is on the order of the noise shaping filter.
  • a suitable threshold is 0.1.
  • the remaining reflection coefficients are typically converted to linear prediction coefficients, which technique is also known as a "step-up" procedure.
  • the calculated LPC coefficients are then used as coder noise shaping filter coefficients, ie as prediction filter coefficients.
  • This FIR filter is routed over the specified target frequency range.
  • the decoding uses an autoregressive filter, while the coding uses a so-called moving average filter.
  • the page information for the TNS tool is also supplied to the bit stream formatter, as shown by the arrow between the block TNS processing 1010 and the bit stream formatter 1004 in FIG Fig. 3 is shown.
  • the center / side encoder 1012 is active when the audio signal to be encoded is a multi-channel signal, that is, a stereo signal having a left channel and a right channel. So far, ie in the processing direction before block 1012 in FIG Fig. 3 For example, the left and right stereo channels were processed separately, that is, scaled, transformed by the filter bank, or not subjected to TNS processing, etc.
  • middle / side encoder In the middle / side encoder is then first checked whether a middle / side encoding makes sense, that brings a coding gain at all. A middle / side encoding will then bring a coding gain if the left and the right channel are more similar, because then the center channel, that is the sum of the left and the right channel is almost equal to the left or the right channel, apart from the scaling by the factor 1/2, while the page channel has only very small values, since it is equal to the difference between the left and the right channel.
  • the left and right channels are approximately equal, the difference is approximately zero, or includes only very small values that are hopefully quantized to zero in a subsequent quantizer 1014, and thus since the quantizer 1014 is followed by an entropy encoder 1016.
  • the quantizer 1014 is given a allowed perturbation per scale factor band by a psycho-acoustic model 1020.
  • the quantizer operates iteratively, ie it first calls an outer iteration loop, which then calls an inner iteration loop.
  • a quantization of a block of values is made at the input of the quantizer 1014.
  • the inner loop quantizes the MDCT coefficients, consuming a certain number of bits.
  • the outer loop calculates the distortion and modified energy of the coefficients using the scale factor to again invoke an inner loop. This process is iterated until a certain conditional set is satisfied.
  • the signal is reconstructed to compute the perturbation introduced by the quantization and to compare it with the allowable perturbation provided by the psycho-acoustic model 1020. Furthermore, the scale factors are increased from iteration to iteration by one step, for each iteration of the outer iteration loop.
  • the iteration ie the analysis-by-synthesis method is terminated, and the resulting scale factors are encoded as set forth in block 1014 and supplied in coded form to the bitstream formatter 1004 as indicated by the arrow between block 1014 and the block Block 1004 is drawn.
  • the quantized values are then fed to entropy coder 1016, which typically performs entropy coding using several Huffman code tables for different scale factor bands to transmit the quantized values into a binary format.
  • entropy coding in the form of Huffman coding relies on code tables that are created on the basis of expected signal statistics, and that frequently occurring values get shorter code words than less frequent values.
  • the entropy-coded values are then also supplied as actual main information to the bitstream formatter 1004, which then outputs the coded audio signal on the output side according to a specific bit stream syntax.
  • the data reduction of audio signals is now a known technique that is the subject of a number of international standards (e.g., ISO / MPEG-1, MPEG-2 AAC, MPEG-4).
  • the input signal by means of a so-called encoder taking advantage of perceptual effects (psychoacoustics, psycho-optics) is brought into a compact, data-reduced representation.
  • a spectral analysis of the signal is usually carried out and the corresponding signal components are quantized taking into account a perceptual model and then coded in a compact manner as so-called bitstream.
  • PE perceptual entropy
  • the perceptual entropy or demand estimate of information units for encoding a signal can be used to estimate whether the signal is transient or stationary, since transient signals also require more bits to encode than more stationary ones Signals.
  • the estimation of a transient property of a signal is used, for example, to determine a window length decision, such as at block 1008 in FIG Fig. 3 is suggested to perform.
  • Fig. 6 is the Perceptual Entropy calculated according to ISO / IEC IS 13818-7 (MPEG-2 advanced audio coding (AAC)).
  • AAC MPEG-2 advanced audio coding
  • the in Fig. 6 illustrated equation used.
  • the parameter pe stands for the perceptual entropy.
  • width (b) stands for the number of spectral coefficients in the respective band b.
  • e (b) is the energy of the signal in this band.
  • nb (b) is the appropriate masking threshold, or more generally, the allowable disturbance that can be introduced into the signal, for example, by quantization, so that a human listener still hears no or only a negligible disturbance.
  • the bands may differ from the band division of the psychoacoustic model (block 1020 in Fig. 3 ), or it is the so-called scale factor bands (scfb) used in the quantization.
  • the psychoacoustic masking threshold is the energy value that the quantization error should not exceed.
  • FIG. 6 The figure shows how well such a Perceptual Entropy works as an estimate of the number of bits needed for encoding.
  • the respective perceptual entropy was plotted as a function of the consumed bits using the example of an AAC coder at different bit rates for each individual block.
  • the test piece used contains a typical mix of music, language and individual instruments.
  • the points would gather along a straight line through the zero point.
  • the extension of the point sequence with the deviations from the ideal line illustrates the inaccurate estimate.
  • a disadvantage of the in Fig. 6 The concept shown here is therefore the deviation that manifests itself as resulting, for example, in too great a value for the perceptual entropy, which in turn means that the quantizer is signaled that more bits than actually required are needed. This results in the quantizer being too finely quantized that it does not exploit the amount of allowed disturbance, resulting in a reduced coding gain.
  • the value for the Perceptual Entropy is determined to be too small, then the quantizer is signaled that fewer bits than actually required are needed to encode the signal. This, in turn, causes the quantizer to be coarsely quantized, which would immediately result in an audible disturbance in the signal unless countermeasures are taken.
  • the countermeasures can be that the quantizer still requires one or more further iteration loops, which increases the computation time of the coder.
  • Fig. 7 To improve the calculation of Perceptual Entropy you could, as in Fig. 7 is shown, introduce a constant term, such as 1.5, in the logarithmic expression. Then there is already a better result, ie a smaller deviation up or down, although it can still be seen that in the consideration of a constant term in the logarithmic expression, although the case is reduced, the Perceptual Entropy signals too optimistic a need for bits. On the other hand is off Fig. 7 however, it can be clearly seen that significantly too many bits are signaled, which leads to the quantizer always becoming too finely quantized, ie that the bit requirement is assumed to be greater than it actually is, which in turn results in a reduced coding gain.
  • the constant in the logarithmic expression is a rough estimate of the bits needed for the page information.
  • FIG. 8 Another, but very time-consuming computation of Perceptual Entropy is in Fig. 8 shown.
  • Fig. 8 the case is shown in which the perceptual entropy is calculated line by line.
  • the disadvantage lies in the higher computational complexity of the line-by-line calculation.
  • spectral coefficients X (k) are used, where kOffset (b) designates the first index of band b.
  • Fig. 8 With Fig. 7 is compared it can be seen clearly in the range between 2000 and 3000 bits, a reduction of the "rashes" upwards.
  • the PE estimate will therefore be more accurate, so not too pessimistic, but rather at the optimum, so that the coding gain in comparison to the in Fig. 6 and 7 shown Calculation method may increase, or the number of iterations in the quantizer is reduced.
  • the US 2002/103637 A1 discloses a concept for improving the performance of encoding systems employing high frequency reconstruction techniques.
  • an encoding difficulty or a measure of the workload of an encoder is calculated on the encoder side in order to control the crossover frequency which determines up to what frequency a signal is coded with a source coder, the proportion of the signal being above the crossover frequency is encoded by a high frequency reconstruction method.
  • Perceptual Entropy is calculated based on squealing a spectral value and then weighting it with a number equal to the number of lines in the current band divided by the psychoacoustic threshold for it Band is around then to form a logarithm of the result.
  • a distortion energy at the end of the source coding process can also be calculated by summing the distortion energy in each band and weighting it with a loudness curve.
  • the object of the present invention is to provide an efficient yet accurate concept for determining an estimate of a need for information units to encode a signal.
  • the present invention is based on the finding that a frequency band-wise calculation of the estimate for a need for information units must be recorded for computing time reasons, however, in order to obtain an accurate determination of the estimated value, the distribution of the energy in the frequency band should be calculated band-by-band is, must be taken into account.
  • the entropy coder following the quantizer is implicitly "involved" in determining the estimate of the demand for information units.
  • the entropy coding makes it possible that a smaller number of bits is required to transmit smaller spectral values than to transmit larger spectral values.
  • the entropy coder is particularly efficient when it is possible to transmit to-zero-quantized spectral values. Since these are typically on occur most frequently, the codeword for transmitting a zero-quantized spectral line is the shortest codeword, and the codeword for transmitting an ever larger quantized spectral line becomes longer and longer.
  • the measure of the distribution of energy in the frequency band can be determined based on the actual amplitudes, or by estimating the frequency lines that are not quantized to zero by the quantizer.
  • This measure which is also referred to as "nl", where nl stands for “number of active lines", ie for the number of active lines, is preferred for computing efficiency reasons.
  • the number of spectral lines quantized to zero or a finer subdivision can also be taken into account, this estimation The more information of the downstream entropy coder is taken into account, the more accurate it becomes.
  • the entropy coder is constructed on the basis of Huffman code tables, properties of these codetables can be integrated particularly well, since the codetables are not calculated on-line on the basis of the signal statistics, but because the codetables are fixed independently of the actual signal anyway.
  • the measure of the distribution of the energy in the frequency band is carried out by determining the lines still surviving after the quantization, ie the number of active lines.
  • the present invention is advantageous in that an estimate of a need for information content is determined which is more accurate and more efficient than the prior art.
  • the present invention is scalable to various applications because, depending on the desired accuracy of the estimate, more and more characteristics of the entropy coder, but at the cost of increased computation time, can be included in the estimation of the bit demand.
  • the signal is already present as a spectral representation with spectral values.
  • this is not absolutely necessary as it can be achieved by appropriate e.g. Bandpass filtering also some calculations can be done with a time signal.
  • the signal is provided to a device 102 for providing a measure of allowable interference to a frequency band of the signal.
  • the allowed disturbance can, for example, by means of a psycho-acoustic model, as shown by Fig. 3 (Block 1020) has been explained.
  • the device 102 is also operative to also provide a measure of the energy of the signal in the frequency band.
  • the prerequisite for a band-wise calculation is that a frequency band for which an allowable disturbance or a signal energy is specified contains at least two or more spectral lines of the spectral representation of the signal.
  • the frequency band will preferably be a scale factor band, since the bit-demand estimate is needed directly by the quantizer to determine whether or not a done quantization satisfies a bit-criterion.
  • the device 102 is designed to supply both the allowed disturbance nb (b) and the signal energy e (b) of the signal in the band to a device 104 for calculating the demand for bits.
  • the means 104 for calculating the demand for bits is designed to take into account, in addition to the allowable disturbance and the signal energy, a measure nl (b) for a distribution of the energy in the frequency band, the distribution of energy in the frequency band Frequency band deviates from a completely uniform distribution.
  • the measure for the distribution of the energy is calculated in a device 106, wherein the device 106 requires at least one band, namely the considered frequency band of the audio or video signal either as a bandpass signal or directly as a sequence of spectral lines, for example a spectral analysis of the Bandes to be able to get the measure of the distribution of energies in the frequency band.
  • the audio or video signal may be supplied to the device 106 as a time signal, the device 106 then performing band filtering as well as analysis in the band.
  • the audio or video signal supplied to the device 106 may already be in the frequency domain, e.g. as a MDCT coefficient, or as a bandpass signal in the filter bank with a smaller number of bandpass filters compared to an MDCT filter bank.
  • means 106 for calculating is adapted to take into account current amounts of spectral values in the frequency band to calculate the estimate.
  • the means for calculating the measure of the distribution of the energy can be designed to determine as a measure of the distribution of energy a number of spectral values whose magnitude is greater than or equal to a predetermined magnitude threshold, or whose magnitude is less than or equal to the magnitude threshold wherein the magnitude threshold is preferably an estimated quantizer level that causes values in a quantizer to be smaller or quantized to zero equal to the quantizer level.
  • the measure of the energy is the number of active lines, that is, the number of lines that survive after quantization or not equal to zero.
  • Fig. 2a shows a preferred embodiment of the means 106 for calculating the measure of the distribution of energy in the frequency band.
  • the measure of the distribution of energy in the frequency band is in Fig. 2a denoted by nl (b).
  • the form factor ffac (b) is already a measure of the distribution of the energy e (b) or eb or en in the frequency band b.
  • the measure of the spectral distribution nl from the form factor ffac (b) is weighted by the 4th root of the signal energy e (b) divided by the bandwidth width (b) and number of lines, respectively determined in the scale factor band b.
  • the shape factor is also an example of a quantity indicating a measure of the distribution of the energies
  • nl (b) is an example of a quantity containing an estimate of the number of energies represents lines relevant to quantization.
  • the form factor ffac (b) is calculated by absolute value formation of a spectral line and subsequent rooting of this spectral line and subsequent summation of the "rooted" amounts of the spectral lines in the band.
  • Fig. 2b shows a preferred embodiment of the means 104 for calculating the estimated value pe, wherein in Fig. 2b another case distinction is introduced, namely when the base 2 logarithm of the ratio of the energy to the allowed disturbance is greater than a constant one Factor c1 or equal to the constant factor.
  • the alternative above in block 104 is taken, ie the measure of the spectral distribution n1 is multiplied by the logarithm expression.
  • the lower alternative in block 104 of FIG Fig. 2b is used, which additionally has an additive constant c2 and a multiplicative constant c3, which is calculated from the constants c2 and c1.
  • Fig. 4a shows Fig. 4a a band with four spectral lines, all of the same size. The energy in this band is thus distributed evenly across the band.
  • Fig. 4b shows a situation where the energy in the band resides in one spectral line while the other three spectral lines are zero.
  • the band shown could be before quantization, or could be obtained after quantization, if the in Fig. 4b zero spectral lines before quantization are smaller than the first quantizer level and thus set to zero by the quantizer, thus not "survive".
  • nl ie the measure of the spectral distribution of energy in Fig. 4a calculated to 4. This means that the spectral distribution the energy is more uniform if the measure of the distribution of the spectral energy is greater.
  • the invention thus takes into account how the energy is distributed within the band. This is done, as has been done, by replacing the number of lines per band in the known equation ( Fig. 6 ) by estimating the number of lines that are nonzero after quantization. This estimate is in Fig. 2a shown.
  • Fig. 2a is also required elsewhere in the encoder, for example within the quantization block 1014 to determine the quantization step size. Then, if the form factor is already computed elsewhere, it does not need to be recalculated for bit estimation so that the inventive concept for improved estimation of the measure of the required bits with a minimum of additional computational effort.
  • X (k) is the spectral coefficient to be quantized later, while the variable kOffset (b) designates the first index in band b.
  • the new formula for calculating improved band-wise perceptual entropy is thus based on multiplying the measure of the spectral distribution of energy and the logarithmic expression by giving the signal energy e (b) in the numerator and the allowed error in the denominator, as needed a term within the logarithm can be used, as it is already in Fig. 7 is shown.
  • this term may also be 1.5, but may also be zero, as in FIG Fig. 2b shown case, this z. B. can be determined empirically.
  • the method according to the invention can be implemented in hardware or in software.
  • the implementation may be on a digital storage medium, in particular a floppy disk or CD with electronically readable control signals, which may interact with a programmable computer system such that the method is performed.
  • the invention thus also consists in a computer program product with a program code stored on a machine-readable carrier for carrying out the method according to the invention, when the computer program product runs on a computer.
  • the invention can thus be realized as a computer program with a program code for carrying out the method when the computer program runs on a computer.

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EP08021083.4A 2004-03-01 2005-02-17 Dispositif et procédé destinés à déterminer une valeur d'évaluation Active EP2034473B1 (fr)

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PL08021083T PL2034473T3 (pl) 2004-03-01 2005-02-17 Urządzenie i sposób ustalania szacowanej wartości
PL19167397T PL3544003T3 (pl) 2004-03-01 2005-02-17 Urządzenie i sposób ustalania szacowanej wartości
EP19167397.9A EP3544003B1 (fr) 2004-03-01 2005-02-17 Dispositif et procédé de détermination d'une valeur d'évaluation

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DE102004009949A DE102004009949B4 (de) 2004-03-01 2004-03-01 Vorrichtung und Verfahren zum Ermitteln eines Schätzwertes
PCT/EP2005/001651 WO2005083680A1 (fr) 2004-03-01 2005-02-17 Dispositif et procede pour determiner une valeur estimee
EP05707481A EP1697931B1 (fr) 2004-03-01 2005-02-17 Dispositif et procede pour determiner une valeur estimee

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US7318028B2 (en) 2008-01-08
US20070129940A1 (en) 2007-06-07
RU2337414C2 (ru) 2008-10-27
AU2005217507B2 (en) 2008-08-14
CA2559354C (fr) 2011-08-02
AU2005217507A1 (en) 2005-09-09
BRPI0507815A (pt) 2007-07-10
ES2376887T3 (es) 2012-03-20
IL176978A0 (en) 2006-12-10
HK1093813A1 (en) 2007-03-09
EP1697931B1 (fr) 2011-11-02
CA2559354A1 (fr) 2005-09-09
EP1697931A1 (fr) 2006-09-06
ATE532173T1 (de) 2011-11-15
PL2034473T3 (pl) 2019-11-29
CN1938758A (zh) 2007-03-28
JP4673882B2 (ja) 2011-04-20
JP2007525715A (ja) 2007-09-06
PL3544003T3 (pl) 2021-07-12
EP2034473B1 (fr) 2019-05-15
DE102004009949A1 (de) 2005-09-29
DE102004009949B4 (de) 2006-03-09
IL176978A (en) 2012-08-30
CN1938758B (zh) 2010-11-10
RU2006134638A (ru) 2008-04-10
EP2034473A3 (fr) 2015-09-16
ES2739544T3 (es) 2020-01-31
PT3544003T (pt) 2021-02-04
KR100852482B1 (ko) 2008-08-18
NO20064432L (no) 2006-09-29
DK1697931T3 (da) 2012-02-27
EP3544003A1 (fr) 2019-09-25
BRPI0507815B1 (pt) 2018-09-11
ES2847237T3 (es) 2021-08-02
PT2034473T (pt) 2019-08-05
NO338917B1 (no) 2016-10-31
KR20060121978A (ko) 2006-11-29
WO2005083680A1 (fr) 2005-09-09
EP3544003B1 (fr) 2020-12-23

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