Classifications

• • G—PHYSICS
  • G10—MUSICAL INSTRUMENTS; ACOUSTICS
  • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; 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
  • G10L19/008—Multichannel audio signal coding or decoding using interchannel correlation to reduce redundancy, e.g. joint-stereo, intensity-coding or matrixing
• • G—PHYSICS
  • G10—MUSICAL INSTRUMENTS; ACOUSTICS
  • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; 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
  • G10L19/012—Comfort noise or silence coding
• • G—PHYSICS
  • G10—MUSICAL INSTRUMENTS; ACOUSTICS
  • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; 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
  • G10L19/0212—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 using orthogonal transformation
• • G—PHYSICS
  • G10—MUSICAL INSTRUMENTS; ACOUSTICS
  • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; 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
  • G10L19/032—Quantisation or dequantisation of spectral components
  • G10L19/038—Vector quantisation, e.g. TwinVQ audio
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04S—STEREOPHONIC SYSTEMS 
  • H04S3/00—Systems employing more than two channels, e.g. quadraphonic
  • H04S3/02—Systems employing more than two channels, e.g. quadraphonic of the matrix type, i.e. in which input signals are combined algebraically, e.g. after having been phase shifted with respect to each other
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04S—STEREOPHONIC SYSTEMS 
  • H04S2420/00—Techniques used stereophonic systems covered by H04S but not provided for in its groups
  • H04S2420/11—Application of ambisonics in stereophonic audio systems

Definitions

• This invention relates to a method and an apparatus for encoding multi-channel Higher Order Ambisonics audio signals for noise reduction, and to a method and an apparatus for decoding multi-channel Higher Order Ambisonics audio signals for noise reduction.
• HOA Higher Order Ambisonics
• HOA signals are multi-channel audio signals.
• the playback of certain multichannel audio signal representations, particularly HOA representations, on a particular loudspeaker set-up requires a special rendering, which usually consists of a matrixing operation.
• the Ambisonics signals are "matrixed", i.e. mapped to new audio signals corresponding to actual spatial positions, e.g. of loudspeakers.
• a usual method for the compression of Higher Order Ambisonics audio signal representations is to apply independent perceptual coders to the individual Ambisonics coeffcient channels [7].
• the perceptual coders only consider coding noise masking effects which occur within each individual single- channel signals. However, such effects are typically non-linear. If matrixing such single-channels into new signals, noise unmasking is likely to occur. This effect also occurs when the Higher Order Ambisonics signals are transformed to the spatial domain by the Discrete Spherical Harmonics Transform prior to
• matrixing origins from the fact that y( is, mathematically, obtained from x( through a matrix operation
• A denotes a mixing matrix composed of mixing weights.
• the terms “mixing” and “matrixing” are used synonymously herein. Mixing/matrixing is used for the purpose of rendering audio signals for any particular loudspeaker setups.
• the present invention provides an improvement to encoding and/or decoding multi-channel Higher Order Ambisonics audio signals so as to obtain noise reduction.
• the invention provides a way to suppress coding noise de- masking for 3D audio rate compression.
• the invention describes technologies for an adaptive Discrete Spherical
• aDSHT Harmonics Transform
• KLT Karhunen Loeve transform
• a method for encoding multichannel HOA audio signals for noise reduction comprises steps of decorrelating the channels using an inverse adaptive DSHT, the inverse adaptive DSHT comprising a rotation operation and an inverse DSHT (iDSHT), with the rotation operation rotating the spatial sampling grid of the iDSHT, perceptually encoding each of the decorrelated channels, encoding rotation information, the rotation information comprising parameters defining said rotation operation, and transmitting or storing the perceptually encoded audio channels and the encoded rotation information.
• the step of decorrelating the channels using an inverse adaptive DSHT is in principle a spatial encoding step.
• a method for decoding coded multi-channel HOA audio signals with reduced noise comprises steps of receiving encoded multi-channel HOA audio signals and channel rotation information, decompressing the received data, wherein perceptual decoding is used, spatially decoding each channel using an adaptive DSHT (aDSHT), correlating the perceptually and spatially decoded channels, wherein a rotation of a spatial sampling grid of the aDSHT according to said rotation information is performed, and matrixing the correlated perceptually and spatially decoded channels, wherein reproducible audio signals mapped to loudspeaker positions are obtained.
• aDSHT adaptive DSHT
• An apparatus for encoding multi-channel HOA audio signals is disclosed in claim 1 1 .
• An apparatus for decoding multi-channel HOA audio signals is disclosed in claim 12.
• a computer readable medium has executable instructions to cause a computer to perform a method for encoding comprising steps as disclosed above, or to perform a method for decoding comprising steps as disclosed above.
• Fig.1 a known encoder and decoder for rate compressing a block of M
• Fig.2 a known encoder and decoder for transforming a HOA signal into the spatial domain using a conventional DSHT (Discrete Spherical Harmonics
• Fig.3 an encoder and decoder for transforming a HOA signal into the spatial
• Fig.6 signal adaptive DSHT building blocks (pE and pD)
• Fig.7 a first embodiment of the present invention
• FIG.8 flow-charts of an encoding process and a decoding process
• Fig.9 a second embodiment of the present invention.
• Fig.2 shows a known system where a HOA signal is transformed into the spatial domain using an inverse DSHT.
• the signal is subject to transformation using iDSHT 21 , rate compression E1 / decompression D1 , and re-transformed to the coefficient domain S24 using the DSHT 24.
• Fig.3 shows a system according to one embodiment of the present invention:
• the DSHT processing blocks of the known solution are replaced by processing blocks 31 ,34 that control an inverse adaptive DSHT and an adaptive DSHT, respectively.
• Side infornnation SI is transmitted within the bitstream bs.
• the system comprises elements of an apparatus for encoding multi-channel HOA audio signals and elements of an apparatus for decoding multi-channel HOA audio signals.
• an apparatus ENC for encoding multi-channel HOA audio signals for noise reduction includes a decorrelator 31 for decorrelating the channels B using an inverse adaptive DSHT (iaDSHT), the inverse adaptive DSHT including a rotation operation unit 31 1 and an inverse DSHT (iDSHT) 310.
• the rotation operation unit rotates the spatial sampling grid of the iDSHT.
• the decorrelator 31 provides decorrelated channels W sd and side information SI that includes rotation information.
• the apparatus includes a perceptual encoder 32 for perceptually encoding each of the decorrelated channels W sd , and a side information encoder 321 for encoding rotation information.
• the rotation information comprises parameters defining said rotation operation.
• the perceptual encoder 32 provides perceptually encoded audio channels and the encoded rotation information, thus reducing the data rate.
• the apparatus for encoding comprises interface means 320 for creating a bitstream bs from the perceptually encoded audio channels and the encoded rotation information and for transmitting or storing the bitstream bs.
• An apparatus DEC for decoding multi-channel HOA audio signals with reduced noise includes interface means 330 for receiving encoded multi-channel HOA audio signals and channel rotation information, and a decompression module 33 for decompressing the received data, which includes a perceptual decoder for perceptually decoding each channel.
• the decompression module 33 provides recovered perceptually decoded channels W' sd and recovered side information SI'.
• the apparatus for decoding includes a correlator 34 for correlating the perceptually decoded channels W' sd using an adaptive DSHT (aDSHT), wherein a DSHT and a rotation of a spatial sampling grid of the DSHT according to said rotation information are performed, and a mixer MX for matrixing the correlated perceptually decoded channels, wherein reproducible audio signals mapped to loudspeaker positions are obtained.
• aDSHT can be performed in a DSHT unit 340 within the correlator 34.
• the rotation of the spatial sampling grid is done in a grid rotation unit 341 , which in principle recalculates the original DSHT sampling points.
• the rotation is performed within the DSHT unit 340.
• the matrix of the reconstructed frame samples which is denoted by X , is composed of the true sample matrix X and an coding noise component E according to
• a further essential assumption is that the coding is performed such that a predefined signal-to-noise ratio (SNR) is satisfied for each channel.
• SNR signal-to-noise ratio
• N the matrix containing the samples of the matrixed noise signals. It can be expressed as
• n(m): [n ⁇ m) ... n j (m)] T (17) is the vector of all matrixed noise signals at the time sample index m .
• Equation (1 1 ) the empirical correlation matrix of the matrixed noise-free signals can be formulated as
• this SNR is obtained from the predefined SNR, SNR X , by the multiplication with a term, which is dependent on the diagonal and non-diagonal component of the signal correlation matrix ⁇ x .
• the empirical SNR of the matrixed signals is equal to the predefined SNR if the signals Xi(m) are uncorrelated to each other such that ⁇ X NG becomes a zero matrix, i.e.,
• HOA Higher Order Ambisonics
• SHs Spherical Harmonics
• j n (-) indicate the spherical Bessel functions of the first kind and order n and ⁇ TM( ⁇ ) denote the Spherical Harmonics (SH) of order n and degree m.
• SH Spherical Harmonics
• SHs are complex valued functions in general.
• a source field can be defined as:
• a source field can consist of far- field/ near-field, discrete/ continuous sources [1 ].
• the source field coefficients BTM are related to the sound field coefficients A% by, [1 ]:
• Signals in the HOA domain can be represented in frequency domain or in time domain as the inverse Fourier transform of the source field or sound f/ ' eld coefficients.
• the following description will assume the use of a time domain representation of source field coefficients:
• K F t ⁇ 5 ⁇ (35) of a finite number:
• the number of coefficients (or HOA channels) is given by:
• the coefficients bTM comprise the Audio information of one time sample m for later reproduction by loudspeakers. They can be stored or transmitted and are thus subject of data rate compression.
• Equation (33) can be rewritten using time domain HOA coefficients for / discrete spatial sample positions ⁇ .
• ⁇ [6 lt ⁇ 7 on the unit sphere:
• Equation (38) transforms L sd spherical signals into the coefficient domain and can be rewritten as a forward transform:
• rate compression of Higer Order Ambisonics coefficient data and noise unmasking is described.
• a test signal is defined to highlight some properties, which is used below.
• test signal B g can be seen as the simplest case of an HOA signal. More complex signals consist of a superposition of many of such signals. Concerning direct compression of HOA channels, the following shows why noise unmasking occurs when HOA coefficient channels are compressed. Direct compression and decompression of the 0 3D coefficient channels of an actual block of HOA data B will introduce coding noise E analogous to equation (4):
• W sd ⁇ ⁇ B , (50) with inverse transform matrix ⁇ ; related to the L SD ⁇ 0 3D spatial sample positions, and spatial signal matrix W SH ⁇ C isdX .
• Equation (53) should be seen analogous to equation (14). Again applying all considerations described above, the SNR of speaker channel / can be described by (analogous to equation (29)):
• a basic idea of the present invention is to minimize noise unmasking effects by using an adaptive DSHT (aDSHT), which is composed of a rotation of the spatial sampling grid of the DSHT related to the spatial properties of the HOA input signal, and the DSHT itself.
• aDSHT adaptive DSHT
• a signal adaptive DSHT (aDSHT) with a number of spherical positions L sd matching the number of HOA coefficients 0 3D , (36), is described below.
• aDSHT signal adaptive DSHT
• a default spherical sample grid as in the conventional non-adaptive DSHT is selected.
• the spherical sample grid is rotated such that the logarithm of the term
• this process corresponds to a rotation of the spherical sampling grid of the DSHT in a way that a single spatial sample position matches the strongest source direction, as shown in Fig.4.
• the term W sd of equation (55) becomes a vector ⁇ c isdX1 with all elements close to zero except one. Consequently ⁇ Wsd becomes near diagonal and the desired SNR SNR S can be kept.
• Fig.4 shows a test signal B g transformed to the spatial domain. In Fig.4 a), the default sampling grid was used, and in Fig.4 b), the rotated grid of the aDSHT was used.
• Each cell of the spatial structure represents a sampling point, and the lightness/darkness of the cell represents a signal strength.
• a strongest source direction was found and the sampling grid was rotated such that one of the sides (i.e. a single spatial sample position) matches the strongest source direction. This side is depicted white (corresponding to strong source direction), while the other sides are dark (corresponding to low source direction).
• Fig.4 a i.e. before rotation, no side matches the strongest source direction, and several sides are more or less grey, which means that an audio signal of considerable (but not maximum) strength is received at the respective sampling point.
• the following describes the main building blocks of the aDSHT used within the compression encoder and decoder.
• Fig.5 shows examples of basic grids.
• Input to the rotation finding block (building block 'find best rotation') 320 is the coefficient matrix B.
• the building block is responsible to rotate the basis sampling grid such that the value of eq.(57) is minimized.
• the rotation is represented by the 'axis-angle' representation and compressed axis tp rot and rotation angle (p rot related to this rotation are output to this building block as side information SI.
• the rotation axis tp rot can be described by a unit vector from the origin to a position on the unit sphere.
• the first embodiment makes use of a single aDSHT.
• the second embodiment makes use of multiple aDSHTs in spectral bands.
• the first ("basic") embodiment is shown in Fig.7.
• the HOA time samples with index m of 0 3D coefficient channels b(m) are first stored in a buffer 71 to form blocks of M samples and time index ⁇ .
• ⁇ ( ⁇ ) is transformed to the spatial domain using the adaptive iDSHT in building block pE 72 as described above.
• the spatial signal block W sd (j ) is input to L sd Audio Compression mono encoders 73, like AAC or mp3 encoders, or a single AAC multichannel encoder (L sd channels).
• the bitstream S73 consists of multiplexed frames of multiple encoder bitstream frames with integrated side information SI or a single multichannel bitstream where side information SI is integrated, preferable as auxiliary data.
• a respective compression decoder building block comprises, in one embodiment, demultiplexer D1 for demultiplexing the bitstream S73 to L sd bitstreams and side information SI, and feeding the bitstreams to L sd mono decoders, decoding them to L sd spatial Audio channels with M samples to form block W sd (j ), and feeding W sd (j ) and SI to pD.
• a compression decoder building block comprises a receiver 74 for receiving the bitstream and decoding it to a L sd multichannel signal W sd (j ), depacking SI and feeding W sd (ji) and SI to pD.
• W sd (j ) is transformed using the adaptive DSHTwith SI in the decoder processing block pD 75 to the coefficient domain to form a block of HOA signals ⁇ ( ⁇ ), which are stored in a buffer 76 to be deframed to form a time signal of coefficients b(m).
• the above-described first embodiment may have, under certain conditions, two drawbacks: First, due to changes of spatial signal distribution there can be blocking artifacts from a previous block (i.e. from block ⁇ to ⁇ + 1). Second, there can be more than one strong signals at the same time and the de-correlation effects of the aDSHT are quite small.
• the aDSHT is applied to scale factor band data, which combine multiple frequency band data.
• the blocking artifacts are avoided by the overlapping blocks of the Time to Frequency Transform (TFT) with Overlay Add (OLA) processing.
• TFT Time to Frequency Transform
• OVA Overlay Add
• An improved signal de-correlation can be achieved by using the invention within / spectral bands at the cost of an increased overhead in data rate to transmit Slj.
• Modified Cosine Transform (MDCT).
• a TFT Framing unit 91 1 50% overlapping data blocks (block index ⁇ ) are constructed.
• a TFT block transform unit 912 performs a block transform.
• a Spectral Banding unit 913 the TFT frequency bands are combined to form J new spectral bands and related signals ⁇ ] ⁇ ) ⁇ c° 3D XK) , where K ⁇ denotes the number of frequency coefficients in band j.
• These spectral bands are processed in a plurality of processing blocks 914. For each of these spectral bands, there is one processing block pE that creates signals Wj ( ⁇ ) £ c Lsd XK) and side information Sl j.
• the spectral bands may match the spectral bands of the lossy audio compression method (like AAC/mp3 scale- factor bands), or have a more coarse granularity. In the latter case, the Channel- independent lossy audio compression without TFT block 915 needs to rearrange the banding.
• the processing block 914 acts like a L sd multichannel audio encoder in frequency domain that allocates a constant bit-rate to each audio channel.
• a bitstream is formatted in a bitstream packing block 916.
• the decoder receives or stores the bitstream (at least portions thereof), depacks 921 it and feeds the audio data to the multichannel audio decoder 922 for
• the audio decoder 922 for channel independent Audio decoding without TFT decodes the audio information and formats the / spectral band signals Wj ( ⁇ ) as an input to the decoding processing blocks pD j 923, where these signals are transformed to the HOA coefficient domain to form ⁇ ] ( ⁇ ).
• the J spectral bands are regrouped to match the banding of the TFT. They are transformed to the time domain in the iTFT & OLA block 925, which uses block overlapping Overlay Add (OLA) processing.
• the output of the iTFT & OLA block 925 is de-framed in a TFT Deframing block 926 to create the signal b(m) .
• the present invention is based on the finding that the SNR increase results from cross-correlation between channels.
• the perceptual coders only consider coding noise masking effects that occur within each individual single-channel signals. However, such effects are typically non-linear. Thus, when matrixing such single channels into new signals, noise unmasking is likely to occur. This is the reason why coding noise is normally increased after the matrixing operation.
• the invention proposes a decorrelation of the channels by an adaptive Discrete Spherical Harmonics Transform (aDSHT) that minimizes the unwanted noise unmasking effects.
• the aDSHT is integrated within the compressive coder and decoder architecture. It is adaptive since it includes a rotation operation that adjusts the spatial sampling grid of the DSHT to the spatial properties of the HOA input signal.
• the aDSHT comprises the adaptive rotation and an actual, conventional DSHT.
• the actual DSHT is a matrix that can be constructed as described in the prior art.
• the adaptive rotation is applied to the matrix, which leads to a minimization of inter-channel correlation, and therefore minimization of SNR increase after the matrixing.
• the rotation axis and angle are found by an automized search operation, not analytically.
• the rotation axis and angle are encoded and transmitted, in order to enable re-correlation after decoding and before matrixing, wherein inverse adaptive DSHT (iaDSHT) is used.
• Time-to-Frequency Transfrom (TFT) and spectral banding are performed, and the aDSHT/iaDSHT are applied to each spectral band independently.
• Fig.8 a shows a flow-chart of a method for encoding multi-channel HOA audio signals for noise reduction in one embodiment of the invention.
• Fig.8 b shows a flow-chart of a method for decoding multi-channel HOA audio signals for noise reduction in one embodiment of the invention.
• a method for encoding multi-channel HOA audio signals for noise reduction comprises steps of decorrelating 81 the channels using an inverse adaptive DSHT, the inverse adaptive DSHT comprising a rotation operation and an inverse DSHT 812, with the rotation operation rotating 81 1 the spatial sampling grid of the iDSHT, perceptually encoding 82 each of the decorrelated channels, encoding 83 rotation information (as side information SI), the rotation information comprising parameters defining said rotation operation, and transmitting or storing 84 the perceptually encoded audio channels and the encoded rotation information.
• the inverse adaptive DSHT comprises steps of selecting an initial default spherical sample grid, determining a strongest source direction, and rotating, for a block of M time samples, the spherical sample grid such that a single spatial sample position matches the strongest source direction.
• the spherical sample grid is rotated such that the logarithm of the term
• a method for decoding coded multi-channel HOA audio signals with reduced noise comprises steps of receiving 85 encoded multi-channel HOA audio signals and channel rotation information (within side information SI), decompressing 86 the received data, wherein perceptual decoding is used, spatially decoding 87 each channel using an adaptive DSHT, wherein a DSHT 872 and a rotation 871 of a spatial sampling grid of the DSHT according to said rotation information are performed and wherein the perceptually decoded channels are recorrelated, and matrixing 88 the recorrelated perceptually decoded channels, wherein reproducible audio signals mapped to loudspeaker positions are obtained.
• the adaptive DSHT comprises steps of selecting an initial default spherical sample grid for the adaptive DSHT and rotating, for a block of M time samples, the spherical sample grid according to said rotation information.
• the rotation information is a spatial vector i/j rot with three components. Note that the rotation axis tp rot can be described by a unit vector.
• the rotation information is a vector composed out of 3 angles: ⁇ axis > ⁇ axis > rot > where e axis , 4> axis define the information for the rotation axis with an implicit radius of one in spherical coordinates, and ⁇ p rot defines the rotation angle around this axis.
• angles are quantized and entropy coded with an escape pattern (i.e. dedicated bit pattern) that signals (i.e. indicates) the reuse of previous values for creating side information (SI).
• escape pattern i.e. dedicated bit pattern
• an apparatus for encoding multi-channel HOA audio signals for noise reduction comprises a decorrelator for decorrelating the channels using an inverse adaptive DSHT, the inverse adaptive DSHT comprising a rotation operation and an inverse DSHT (iDSHT), with the rotation operation rotating the spatial sampling grid of the iDSHT; a perceptual encoder for perceptually encoding each of the decorrelated channels, a side information encoder for encoding rotation information, with the rotation information comprising parameters defining said rotation operation, and an interface for transmitting or storing the perceptually encoded audio channels and the encoded rotation information.
• iDSHT inverse DSHT
• an apparatus for decoding multi-channel HOA audio signals with reduced noise comprises interface means 330 for receiving encoded multichannel HOA audio signals and channel rotation information, a decompression module 33 for decompressing the received data by using a perceptual decoder for perceptually decoding each channel, a correlator 34 for re-correlating the perceptually decoded channels, wherein a DSHT and a rotation of a spatial sampling grid of the DSHT according to said rotation information are performed, and a mixer for matrixing the correlated perceptually decoded channels, wherein reproducible audio signals mapped to loudspeaker positions are obtained.
• the correlator 34 acts as a spatial decoder.
• an apparatus for decoding multi-channel HOA audio signals with reduced noise comprises interface means 330 for receiving encoded multichannel HOA audio signals and channel rotation information; decompression module 33 for decompressing the received data with a perceptual decoder for perceptually decoding each channel; a correlator 34 for correlating the
• the adaptive DSHT in the apparatus for decoding comprises means for selecting an initial default spherical sample grid for the adaptive DSHT; rotation processing means for rotating, for a block of M time samples, the default spherical sample grid according to said rotation information; and transform processing means for performing the DSHT on the rotated spherical sample grid.
• the correlator 34 in the apparatus for decoding comprises a plurality of spatial decoding units 922 for simultaneously spatially decoding each channel using an adaptive DSHT, further comprising a spectral debanding unit 924 for performing spectral debanding, and an iTFT&OLA unit 925 for performing an inverse Time to Frequency Transform with Overlay Add processing, wherein the spectral debanding unit provides its output to the iTFT&OLA unit.
• the term reduced noise relates at least to an avoidance of coding noise unmasking.
• Perceptual coding of audio signals means a coding that is adapted to the human perception of audio. It should be noted that when perceptually coding the audio signals, a quantization is usually performed not on the broadband audio signal samples, but rather in individual frequency bands related to the human perception. Hence, the ratio between the signal power and the quantization noise may vary between the individual frequency bands. Thus, perceptual coding usually comprises reduction of redundancy and/or irrelevancy information, while spatial coding usually relates to a spatial relation among the channels.
• KLT Karhunen-Loeve-Transformation
• Definition B is a N order HOA signal matrix, (N + l) 2 rows (coefficients), T columns (time samples); W is a spatial matrix with (N + l) 2 rows (channels), T columns (time samples)
• the transform matrix is the
• the rotation is signal driven and
• the spatial signals are lossy
• the spatial signals are lossy decompressed coded, (coding noise E cod ) .
• a spatial signal block of T samples is arranges as block of T samples is arranges as W k
• the grid is rotated such that a sampling
• signal tracking models can be used that also allow to adapt/modify the rotations smoothly from block to block, which avoids creation of blocking artifacts within the lossy (perceptual) coding blocks

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