Patent Description:
The invention relates to a method and to an apparatus for compressing and decompressing a Higher Order Ambisonics representation by processing directional and ambient signal components differently.

Higher Order Ambisonics (HOA) offers one possibility to represent three-dimensional sound among other techniques like wave field synthesis (WFS) or channel based approaches like <NUM>.

In contrast to channel based methods, however, the HOA representation offers the advantage of being independent of a specific loudspeaker set-up. This flexibility, however, is at the expense of a decoding process which is required for the playback of the HOA representation on a particular loudspeaker set-up. Compared to the WFS approach, where the number of required loudspeakers is usually very large, HOA may also be rendered to set-ups consisting of only few loudspeakers. A further advantage of HOA is that the same representation can also be employed without any modification for binaural rendering to head-phones.

HOA is based on the representation of the spatial density of complex harmonic plane wave amplitudes by a truncated Spherical Harmonics (SH) expansion. Each expansion coefficient is a function of angular frequency, which can be equivalently represented by a time domain function. Hence, without loss of generality, the complete HOA sound field representation actually can be assumed to consist of <NUM> time domain functions, where O denotes the number of expansion coefficients. These time domain functions will be equivalently referred to as HOA coefficient sequences or as HOA channels.

The spatial resolution of the HOA representation improves with a growing maximum order N of the expansion. Unfortunately, the number of expansion coefficients O grows quadratically with the order N, in particular <NUM> = (N + <NUM>)<NUM>. For example, typical HOA representations using order N = <NUM> require O = <NUM> HOA (expansion) coefficients. According to the previously made considerations, the total bit rate for the transmission of HOA representation, given a desired single-channel sampling rate fs and the number of bits Nb per sample, is determined by O·fs·Nb. Consequently, transmitting an HOA representation of order N = <NUM> with a sampling rate of fs = <NUM> employing Nb = <NUM> bits per sample results in a bit rate of <NUM> MBits/s, which is very high for many practical applications, e.g. for streaming.

Compression of HOA sound field representations is proposed in patent applications <CIT>, <CIT> and <CIT>. Instead of perceptually coding each one of the HOA coefficient sequences individually, as it is performed e.g. in E. Hellerud, I. Burnett, A. Solvang and U. Svensson, "Encoding Higher Order Ambisonics with AAC", 124th AES Convention, Amsterdam, <NUM>, it is attempted to reduce the number of signals to be perceptually coded, in particular by performing a sound field analysis and decomposing the given HOA representation into a directional and a residual ambient component. The directional component is in general supposed to be represented by a small number of dominant directional signals which can be regarded as general plane wave functions. The order of the residual ambient HOA component is reduced because it is assumed that, after the extraction of the dominant directional signals, the lower-order HOA coefficients are carrying the most relevant information.

Altogether, by such operation the initial number (N + <NUM>)<NUM> of HOA coefficient sequences to be perceptually coded is reduced to a fixed number of D dominant directional signals and a number of (NRED + <NUM>)<NUM> HOA coefficient sequences representing the residual ambient HOA component with a truncated order NRED < N, whereby the number of signals to be coded is fixed, i.e. D + (NRED + <NUM>)<NUM>. In particular, this number is independent of the actually detected number DACT(k) ≤ D of active dominant directional sound sources in a time frame k. This means that in time frames k, where the actually detected number DACT(k) of active dominant directional sound sources is smaller than the maximum allowed number D of directional signals, some or even all of the dominant directional signals to be perceptually coded are zero. Ultimately, this means that these channels are not used at all for capturing the relevant information of the sound field.

In this context, a further possibly weak point in the <CIT> and <CIT> processings is the criterion for the determination of the amount of active dominant directional signals in each time frame, because it is not attempted to determine an optimal amount of active dominant directional signals with respect to the successive perceptual coding of the sound field. For instance, in <CIT> the amount of dominant sound sources is estimated using a simple power criterion, namely by determining the dimension of the subspace of the inter-coefficients correlation matrix belonging to the greatest eigenvalues. In <CIT> an incremental detection of dominant directional sound sources is proposed, where a directional sound source is considered to be dominant if the power of the plane wave function from the respective direction is high enough with respect to the first directional signal. Using power based criteria like in <CIT> and <CIT> may lead to a directional-ambient decomposition which is suboptimal with respect to perceptual coding of the sound field.

A problem to be solved by the invention is to improve HOA compression by determining for a current HOA audio signal content how to assign to a predetermined reduced number of channels, directional signals and coefficients for the ambient HOA component. This problem is solved by the methods and apparatuses that are disclosed in the respective independent claims.

The invention improves the compression processing proposed in <CIT> in two aspects. First, the bandwidth provided by the given number of channels to be perceptually coded is better exploited. In time frames where no dominant sound source signals are detected, the channels originally reserved for the dominant directional signals are used for capturing additional information about the ambient component, in the form of additional HOA coefficient sequences of the residual ambient HOA component. Second, having in mind the goal to exploit a given number of channels to perceptually code a given HOA sound field representation, the criterion for the determination of the amount of directional signals to be extracted from the HOA representation is adapted with respect to that purpose. The number of directional signals is determined such that the decoded and reconstructed HOA representation provides the lowest perceptible error. That criterion compares the modelling errors arising either from extracting a directional signal and using a HOA coefficient sequence less for describing the residual ambient HOA component, or arising from not extracting a directional signal and instead using an additional HOA coefficient sequence for describing the residual ambient HOA component. That criterion further considers for both cases the spatial power distribution of the quantisation noise introduced by the perceptual coding of the directional signals and the HOA coefficient sequences of the residual ambient HOA component.

In order to implement the above-described processing, before starting the HOA compression, a total number I of signals (channels) is specified compared to which the original number of O HOA coefficient sequences is reduced. The ambient HOA component is assumed to be represented by a minimum number ORED of HOA coefficient sequences. In some cases, that minimum number can be zero. The remaining D = I - ORED channels are supposed to contain either directional signals or additional coefficient sequences of the ambient HOA component, depending on what the directional signal extraction processing decides to be perceptually more meaningful. It is assumed that the assigning of either directional signals or ambient HOA component coefficient sequences to the remaining D channels can change on frame-by-frame basis. For reconstruction of the sound field at receiver side, information about the assignment is transmitted as extra side information.

A method for decompressing a compressed Higher Order Ambisonics representation is disclosed in claim <NUM>. An apparatus for decompressing a Higher Order Ambisonics representation is disclosed in claim <NUM>.

Exemplary embodiments of the invention are described with reference to the accompanying drawings, which show in:.

The compression processing according to the invention, which is based on <CIT>, is illustrated in <FIG> where the signal processing blocks that have been modified or newly introduced compared to <CIT> are presented with a bold box, and where '<IMG>' (direction estimates as such) and 'C' in this application correspond to 'A' (matrix of direction estimates) and 'D' in <CIT>, respectively.

For the HOA compression a frame-wise processing with non-overlapping input frames C(k) of HOA coefficient sequences of length L is used, where k denotes the frame index. The frames are defined with respect to the HOA coefficient sequences specified in equation (<NUM>) as <MAT> where TS indicates the sampling period.

The first step or stage <NUM>/<NUM> in <FIG> is optional and consists of concatenating the non-overlapping k-th and the (k - <NUM>) - th frames of HOA coefficient sequences into a long frame C̃(k) as <MAT> which long frame is <NUM>% overlapped with an adjacent long frame and which long frame is successively used for the estimation of dominant sound source directions. Similar to the notation for C̃(k), the tilde symbol is used in the following description for indicating that the respective quantity refers to long overlapping frames. If step/stage <NUM>/<NUM> is not present, the tilde symbol has no specific meaning.

In principle, the estimation step or stage <NUM> of dominant sound sources is carried out as proposed in <CIT>, but with an important modification. The modification is related to the determination of the amount of directions to be detected, i.e. how many directional signals are supposed to be extracted from the HOA representation. This is accomplished with the motivation to extract directional signals only if it is perceptually more relevant than using instead additional HOA coefficient sequences for better approximation of the ambient HOA component. A detailed description of this technique is given in section A.

The estimation provides a data set <IMG>(k) ⊆ {<NUM>,. , D} of indices of directional signals that have been detected as well as the set <IMG>(k) of corresponding direction estimates. D denotes the maximum number of directional signals that has to be set before starting the HOA compression.

In step or stage <NUM>, the current (long) frame C̃(k) of HOA coefficient sequences is decomposed (as proposed in <CIT>) into a number of directional signals XDIR(k - <NUM>) belonging to the directions contained in the set <IMG>(k), and a residual ambient HOA component CAMB(k - <NUM>). The delay of two frames is introduced as a result of overlap-add processing in order to obtain smooth signals. It is assumed that XDIR(k - <NUM>) is containing a total of D channels, of which however only those corresponding to the active directional signals are non-zero. The indices specifying these channels are assumed to be output in the data set <IMG>(k - <NUM>). Additionally, the decomposition in step/stage <NUM> provides some parameters ζ(k - <NUM>) which are used at decompression side for predicting portions of the original HOA representation from the directional signals (see <CIT> for more details).

In step or stage <NUM>, the number of coefficients of the ambient HOA component CAMB(k - <NUM>) is intelligently reduced to contain only ORED + D -NDIR,ACT(k - <NUM>) non-zero HOA coefficient sequences, where NDIR,ACT(k - <NUM>) = |<IMG>(k - <NUM>)| indicates the cardinality of the data set <IMG>(k - <NUM>), i.e. the number of active directional signals in frame k - <NUM>. Since the ambient HOA component is assumed to be always represented by a minimum number ORED of HOA coefficient sequences, this problem can be actually reduced to the selection of the remaining D - NDIR,ACT(k - <NUM>) HOA coefficient sequences out of the possible O - ORED ones. In order to obtain a smooth reduced ambient HOA representation, this choice is accomplished such that, compared to the choice taken at the previous frame k - <NUM>, as few changes as possible will occur.

In particular, the three following cases are to be differentiated:.

For avoiding discontinuities at frame borders when additional HOA coefficient sequences are activated or deactivated, it is advantageous to smoothly fade in or out the respective signals.

The final ambient HOA representation with the reduced number of <NUM>RED +NDIR,ACT(k - <NUM>) non-zero coefficient sequences is denoted by CAMB,RED(k - <NUM>). The indices of the chosen ambient HOA coefficient sequences are output in the data set <IMG>(k - <NUM>).

In step/stage <NUM>, the active directional signals contained in XDIR(k - <NUM>) and the HOA coefficient sequences contained in CAMB,RED(k - <NUM>) are assigned to the frame Y(k - <NUM>) of I channels for individual perceptual encoding. To describe the signal assignment in more detail, the frames XDIR(k - <NUM>), Y(k - <NUM>) and CAMB,RED(k - <NUM>) are assumed to consist of the individual signals xDIR,d(k- <NUM>), d ∈ {<NUM>,. ,D}, yi(k - <NUM>), i ∈ {<NUM>,. ,<NUM>} and cAMB,RED,o(k - <NUM>), o ∈ {<NUM>,. ,<NUM>} as follows: <MAT>.

The active directional signals are assigned such that they keep their channel indices in order to obtain continuous signals for the successive perceptual coding. This can be expressed by <MAT>.

The HOA coefficient sequences of the ambient component are assigned such the minimum number of ORED coefficient sequences is always contained in the last <NUM>RED signals of Y(k - <NUM>), i.e. <MAT>.

For the additional D - NDIR,ACT(k - <NUM>) HOA coefficient sequences of the ambient component it is to be differentiated whether or not they were also selected in the previous frame:.

Advantageously, this assigning operation also provides the assignment vector <MAT>, whose elements γo(k), o = <NUM>,. ,D - NDIR,ACT(k - <NUM>), denote the indices of each one of the additional D - NDIR,ACT(k - <NUM>) HOA coefficient sequences of the ambient component. To say it differently, the elements of the assignment vector y(k) provide information about which of the additional O - ORED HOA coefficient sequences of the ambient HOA component are assigned into the D - NDIR,ACT(k - <NUM>) channels with inactive directional signals. This vector can be transmitted additionally, but less frequently than by the frame rate, in order to allow for an initialisation of the re-distribution procedure performed for the HOA decompression (see section B). Perceptual coding step/stage <NUM> encodes the I channels of frame Y(k - <NUM>) and outputs an encoded frame Y̌(k - <NUM>).

For frames for which vector γ(k) is not transmitted from step/stage <NUM>, at decompression side the data parameter sets <IMG>(k) and <IMG>(k - <NUM>) instead of vector γ(k) are used for the performing the re-distribution.

The estimation step/stage <NUM> for dominant sound source directions of <FIG> is depicted in <FIG> in more detail. It is essentially performed according to that of <CIT>, but with a decisive difference, which is the way of determining the amount of dominant sound sources, corresponding to the number of directional signals to be extracted from the given HOA representation. This number is significant because it is used for controlling whether the given HOA representation is better represented either by using more directional signals or instead by using more HOA coefficient sequences to better model the ambient HOA component.

The dominant sound source directions estimation starts in step or stage <NUM> with a preliminary search for the dominant sound source directions, using the long frame C̃(k) of input HOA coefficient sequences. Along with the preliminary direction estimates <MAT>, <NUM> ≤ d ≤ D, the corresponding directional signals <MAT> and the HOA sound field components <MAT>, which are supposed to be created by the individual sound sources, are computed as described in <CIT>. In step or stage <NUM>, these quantities are used together with the frame C̃(k) of input HOA coefficient sequences for determining the number D̃(k) of directional signals to be extracted. Consequently, the direction estimates <MAT>, D̃(k) < d ≤ D, the corresponding directional signals <MAT>, and HOA sound field components <MAT> are discarded. Instead, only the direction estimates <MAT>, <NUM> ≤ d ≤ D̃(k) are then assigned to previously found sound sources.

In step or stage <NUM>, the resulting direction trajectories are smoothed according to a sound source movement model and it is determined which ones of the sound sources are supposed to be active (see <CIT>). The last operation provides the set <IMG>(k) of indices of active directional sound sources and the set <IMG>(k) of the corresponding direction estimates.

For determining the number of directional signals in step/stage <NUM>, the situation is assumed that there is a given total amount of I channels which are to be exploited for capturing the perceptually most relevant sound field information. Therefore the number of directional signals to be extracted is determined, motivated by the question whether for the overall HOA compression/decompression quality the current HOA representation is represented better by using either more directional signals, or more HOA coefficient sequences for a better modelling of the ambient HOA component.

To derive in step/stage <NUM> a criterion for the determination of the number of directional sound sources to be extracted, which criterion is related to the human perception, it is taken into consideration that HOA compression is achieved in particular by the following two operations:.

Depending on the number M, <NUM> ≤ M ≤ D, of extracted directional signals, the first operation results in the approximation <MAT> where <MAT> denotes the HOA representation of the directional component consisting of the HOA sound field components <MAT>, <NUM> ≤ d ≤ M, supposed to be created by the M individually considered sound sources, and <MAT> denotes the HOA representation of the ambient component with only I - M non-zero HOA coefficient sequences.

The approximation from the second operation can be expressed by <MAT> <MAT> where <MAT> and <MAT> denote the composed directional and ambient HOA components after perceptual decoding, respectively.

The number D̃(k) of directional signals to be extracted is chosen such that the total approximation error <MAT> with M = D̃(k) is as less significant as possible with respect to the human perception. To assure this, the directional power distribution of the total error for individual Bark scale critical bands is considered at a predefined number Q of test directions Ωq, q = <NUM>,. ,Q, which are nearly uniformly distributed on the unit sphere. To be more specific, the directional power distribution for the b-th critical band, b = <NUM>,. ,B, is represented by the vector <MAT> whose components <MAT> denote the power of the total error
<MAT>
related to the direction Ωq, the b-th Bark scale critical band and the k-th frame. The directional power distribution
<MAT>
of the total error
<MAT>
is compared with the directional perceptual masking power distribution <MAT> due to the original HOA representation C̃(k). Next, for each test direction Ωq and critical band b the level of perception <MAT> of the total error is computed. It is here essentially defined as the ratio of the directional power of the total error
<MAT>
and the directional masking power according to <MAT>.

The subtraction of '<NUM>' and the successive maximum operation is performed to ensure that the perception level is zero, as long as the error power is below the masking threshold.

Finally, the number D̃(k) of directionals signals to be extracted can be chosen to minimise the average over all test directions of the maximum of the error perception level over all critical bands, i.e., <MAT>.

It is noted that, alternatively, it is possible to replace the maximum by an averaging operation in equation (<NUM>).

For the computation of the directional perceptual masking power distribution P̃MASK(k,b) due to the original HOA representation C̃(k), the latter is transformed to the spatial domain in order to be represented by general plane waves ṽq(k) impinging from the test directions Ωq, q = <NUM>,. When arranging the general plane wave signals ṽq(k) in the matrix Ṽ(k) as <MAT> the transformation to the spatial domain is expressed by the operation Ṽ(k) = ΞTC̃(k), (<NUM>)
where Ξ denotes the mode matrix with respect to the test direction Ωq, q = <NUM>,. ,Q, defined by <MAT> with <MAT>.

The elements <IMG>(k,b) of the directional perceptual masking power distribution <IMG>(k,b), due to the original HOA representation C̃(k), are corresponding to the masking powers of the general plane wave functions ṽq(k) for individual critical bands b.

In the following two alternatives for the computation of the directional power distribution <IMG>(k,b) are presented:.

The following describes how to compute the directional power distributions of the three errors for individual Bark scale critical bands:.

The corresponding HOA decompression processing is depicted in <FIG> and includes the following steps or stages.

In step or stage <NUM> a perceptual decoding of the I signals contained in Y̌(k -<NUM>) is performed in order to obtain the I decoded signals in Ŷ(k - <NUM>).

In signal re-distributing step or stage <NUM>, the perceptually decoded signals in Ŷ(k - <NUM>) are re-distributed in order to recreate the frame XDIR(k - <NUM>) of directional signals and the frame ĈAMB,RED(k - <NUM>) of the ambient HOA component. The information about how to re-distribute the signals is obtained by reproducing the assigning operation performed for the HOA compression, using the index data sets J̃DIR,ACT(k) and JAMB,ACT (k - <NUM>). Since this is a recursive procedure (see section A), the additionally transmitted assignment vector γ(k) can be used in order to allow for an initialisation of the re-distribution procedure, e.g. in case the transmission is breaking down.

In composition step or stage <NUM>, a current frame Ĉ(k -<NUM>) of the desired total HOA representation is re-composed (according to the processing described in connection with Fig. 2b and <FIG> of <CIT> using the frame X̂DIR(k - <NUM>) of the directional signals, the set <IMG>(k) of the active directional signal indices together with the set <IMG>(k) of the corresponding directions, the parameters ζ(k - <NUM>) for predicting portions of the HOA representation from the directional signals, and the frame ĈAMB,RED (k - <NUM>) of HOA coefficient sequences of the reduced ambient HOA component. ĈAMB,RED (k - <NUM>) corresponds to component D̂A(k - <NUM>) in <CIT>, and <IMG>(k) and <IMG>(k) correspond to AΩ̂(k) in <CIT>, wherein active directional signal indices are marked in the matrix elements of AΩ̂(k). , directional signals with respect to uniformly distributed directions are predicted from the directional signals (X̂DIR(k - <NUM>)) using the received parameters (ζ(k - <NUM>)) for such prediction, and thereafter the current decompressed frame (Ĉ(k - <NUM>)) is re-composed from the frame of directional signals (X̂DIR(k - <NUM>)), the predicted portions and the reduced ambient HOA component (ĈAMB,RED (k - <NUM>)).

Higher Order Ambisonics (HOA) is based on the description of a sound field within a compact area of interest, which is assumed to be free of sound sources. In that case the spatiotemporal behaviour of the sound pressure p(t,x) at time t and position x within the area of interest is physically fully determined by the homogeneous wave equation. In the following a spherical coordinate system as shown in <FIG> is assumed. In the used coordinate system the x axis points to the frontal position, the γ axis points to the left, and the z axis points to the top. A position in space x = (r,θ,φ)T is represented by a radius r > <NUM> (i.e. the distance to the coordinate origin), an inclination angle θ ∈ [<NUM>, π] measured from the polar axis z and an azimuth angle φ ∈ [<NUM>, 2π[ measured counter-clockwise in the x - y plane from the x axis. Further, (·)T denotes the transposition. It can be shown (see <NPL>) that the Fourier transform of the sound pressure with respect to time denoted by Ft(·), i.e. <MAT> with ω denoting the angular frequency and i indicating the imaginary unit, can be expanded into a series of Spherical Harmonics according to <MAT>.

In equation (<NUM>), cs denotes the speed of sound and k denotes the angular wave number, which is related to the angular frequency ω by <MAT>. Further, jn(·) denote the spherical Bessel functions of the first kind and <MAT> denote the real valued Spherical Harmonics of order n and degree m, which are defined in below section C. The expansion coefficients <MAT> are depending only on the angular wave number k. In the foregoing it has been implicitly assumed that sound pressure is spatially band-limited. Thus the series of Spherical Harmonics is truncated with respect to the order index n at an upper limit N, which is called the order of the HOA representation.

If the sound field is represented by a superposition of an infinite number of harmonic plane waves of different angular frequencies ω arriving from all possible directions specified by the angle tuple (θ,φ), it can be shown (see B. Rafaely, "<NPL>) that the respective plane wave complex amplitude function C(ω,θ,φ) can be expressed by the following Spherical Harmonics expansion <MAT> where the expansion coefficients <MAT> are related to the expansion coefficients <MAT> by <MAT>. (<NUM>) Assuming the individual coefficients <MAT> to be functions of the angular frequency ω, the application of the inverse Fourier transform (denoted by F-<NUM>(·)) provides time domain functions <MAT> for each order n and degree m, which can be collected in a single vector c(t) by <MAT>(<NUM>) <MAT>.

The position index of a time domain function <MAT> within the vector c(t) is given by n(n + <NUM>) + <NUM> + m. The overall number of elements in vector c(t) is given by O = (N + <NUM>)<NUM>.

The final Ambisonics format provides the sampled version of c(t) using a sampling frequency fS as <MAT> where TS = <NUM>/fS denotes the sampling period. The elements of c(lTS) are here referred to as Ambisonics coefficients. The time domain signals <MAT> and hence the Ambisonics coefficients are real-valued.

The real-valued spherical harmonics <MAT> are given by <MAT> <MAT>.

The associated Legendre functions Pn,m(x) are defined as <MAT> with the Legendre polynomial Pn(x) and, unlike in the above-mentioned Williams article, without the Condon-Shortley phase term (-<NUM>)m.

A general plane wave function x(t) arriving from a direction Ω<NUM> = (θ<NUM>,φ<NUM>)T is represented in HOA by <MAT>.

The corresponding spatial density of plane wave amplitudes <MAT> is given by <MAT>.

It can be seen from equation (<NUM>) that it is a product of the general plane wave function x(t) and of a spatial dispersion function vN(Θ), which can be shown to only depend on the angle Θ between Ω and Ω<NUM> having the property <MAT>.

As expected, in the limit of an infinite order, i.e., N → ∞, the spatial dispersion function turns into a Dirac delta δ(·),
i.e. <MAT>.

However, in the case of a finite order N, the contribution of the general plane wave from direction Ω<NUM> is smeared to neighbouring directions, where the extent of the blurring decreases with an increasing order. A plot of the normalised function vN(Θ) for different values of N is shown in <FIG>.

It should be pointed out that for any direction Ω the time domain behaviour of the spatial density of plane wave amplitudes is a multiple of its behaviour at any other direction. In particular, the functions c(t,Ω<NUM>) and c(t,Ω<NUM>) for some fixed directions Ω<NUM> and Ω<NUM> are highly correlated with each other with respect to time t.

If the spatial density of plane wave amplitudes is discretised at a number of O spatial directions Ωo, <NUM> ≤ o ≤ O, which are nearly uniformly distributed on the unit sphere, O directional signals c(t,Ωo) are obtained. Collecting these signals into a vector as <MAT> by using equation (<NUM>) it can be verified that this vector can be computed from the continuous Ambisonics representation d(t) defined in equation (<NUM>) by a simple matrix multiplication as <MAT> where (·)H indicates the joint transposition and conjugation, and Ψ denotes a mode-matrix defined by <MAT> with <MAT>.

Because the directions Ωo are nearly uniformly distributed on the unit sphere, the mode matrix is invertible in general. Hence, the continuous Ambisonics representation can be computed from the directional signals c(t,Ωo) by <MAT>.

Both equations constitute a transform and an inverse transform between the Ambisonics representation and the spatial domain. These transforms are here called the Spherical Harmonic Transform and the inverse Spherical Harmonic Transform.

It should be noted that since the directions Ωo are nearly uniformly distributed on the unit sphere, the approximation <MAT> is available, which justifies the use of Ψ-<NUM> instead of ΨH in equation (<NUM>).

Advantageously, all the mentioned relations are valid for the discrete-time domain, too.

Claim 1:
A method for determining a decompressed Higher Order Ambisonics (HOA) representation from a compressed HOA representation, said method comprising:
receiving a current encoded compressed frame containing the compressed HOA representation;
perceptually decoding (<NUM>) the current encoded compressed frame to provide a perceptually decoded frame (Ŷ(k -<NUM>)) of channels;
re-distributing (<NUM>) said perceptually decoded frame (Ŷ(k - <NUM>)) of channels based on a transmitted assignment vector (γ(k)) indicating at least an index of an additional coefficient sequence of an ambient HOA component in order to re-create a corresponding recreated frame of a residual ambient HOA component (ĈAMB,RED(k - <NUM>)) and a corresponding recreated frame of HOA directional signals (X̂DIR(k - <NUM>));
re-composing (<NUM>) a current decompressed frame (Ĉ(k - <NUM>)) of the HOA representation from the recreated frame of directional signals (X̂DIR(k - <NUM>)) and from the recreated frame of the residual ambient HOA component (ĈAMB,RED(k - <NUM>) based on transmitted indices of detected directional signals (<IMG>(k)) and a transmitted set of dominant direction estimates (<IMG>(k)),
wherein said re-composing the current decompressed frame (Ĉ(k - <NUM>)) is further based on predicted signals that are predicted with respect to uniformly distributed directions from said directional signals (X̂DIR(k - <NUM>)).