Abstract: Higher Order Ambisonics represents three-dimensional sound independent of a specific loudspeaker set-up. However, transmission of an HOA representation results in a very high bit rate. Therefore compression with a fixed number of channels is used, in which directional and ambient signal components are processed differently. For coding, portions of the original HOA representation are predicted from the directional signal components. This prediction provides side information which is required for a corresponding decoding. By using some additional specific purpose bits, a known side information coding processing is improved in that the required number of bits for coding that side information is reduced on average.

Abstract: Higher Order Ambisonics represents three-dimensional sound independent of a specific loudspeaker set-up. However, transmission of an HOA representation results in a very high bit rate. Therefore compression with a fixed number of channels is used, in which directional and ambient signal components are processed differently. The ambient HOA component is represented by a minimum number of HOA coefficient sequences. The remaining channels contain either directional signals or additional coefficient sequences of the ambient HOA component, depending on what will result in optimum perceptual quality. This processing can change on a frame-by-frame basis.

Abstract: A method and apparatus for decompressing a Higher Order Ambisonics (HOA) signal representation is disclosed. The apparatus includes an input interface that receives an encoded directional signal and an encoded ambient signal and an audio decoder that perceptually decodes the encoded directional signal and encoded ambient signal to produce a decoded directional signal and a decoded ambient signal, respectively. The apparatus further includes an extractor for obtaining side information related to the directional signal and an inverse transformer for converting the decoded ambient signal from a spatial domain to an HOA domain representation of the ambient signal. The apparatus also includes a synthesizer for recomposing a Higher Order Ambisonics (HOA) signal from the HOA domain representation of the ambient signal and the decoded directional signal. The side information includes a direction of the directional signal selected from a set of uniformly spaced directions.

Abstract: A method for compressing a HOA signal being an input HOA representation with input time frames (C(k)) of HOA coefficient sequences comprises spatial HOA encoding of the input time frames and subsequent perceptual encoding and source encoding. Each input time frame is decomposed (802) into a frame of predominant sound signals (XPS(k?1)) and a frame of an ambient HOA component ({tilde over (C)}AMB(k?1)). The ambient HOA component ({tilde over (C)}AMB(k?1)) comprises, in a layered mode, first HOA coefficient sequences of the input HOA representation (cn(k?1)) in lower positions and second HOA coefficient sequences (cAMB,n(k?1)) in remaining higher positions. The second HOA coefficient sequences are part of an HOA representation of a residual between the input HOA representation and the HOA representation of the predominant sound signals.

Abstract: A method for compressing a HOA signal being an input HOA representation with input time frames (C(k)) of HOA coefficient sequences comprises spatial HOA encoding of the input time frames and subsequent perceptual encoding and source encoding. Each input time frame is decomposed (802) into a frame of predominant sound signals (XPS(k?1)) and a frame of an ambient HOA component (CAMB (k?1)). The ambient HOA component (CAMB (k?1)) comprises, in a layered mode, first HOA coefficient sequences of the input HOA representation (cn(k?1)) in lower positions and second HOA coefficient sequences (CAMB,n(k?1)) in remaining higher positions. The second HOA coefficient sequences are part of an HOA representation of a residual between the input HOA representation and the HOA representation of the predominant sound signals.

Abstract: When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number (?e) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalization of the HOA data frame representation (C(k)). Then the lowest integer number of bits is set to (AA).

Abstract: Higher Order Ambisonics represents three-dimensional sound independent of a specific loudspeaker set-up. However, transmission of an HOA representation results in a very high bit rate. Therefore compression with a fixed number of channels is used, in which directional and ambient signal components are processed differently. The ambient HOA component is represented by a minimum number of HOA coefficient sequences. The remaining channels contain either directional signals or additional coefficient sequences of the ambient HOA component, depending on what will result in optimum perceptual quality. This processing can change on a frame-by-frame basis.

Abstract: There are two representations for Higher Order Ambisonics denoted HOA: spatial domain and coefficient domain. The invention generates from a coefficient domain representation a mixed spatial/coefficient domain representation, wherein the number of said HOA signals can be variable. A vector of coefficient domain signals is separated into a vector of coefficient domain signals having a constant number of HOA coefficients and a vector of coefficient domain signals having a variable number of HOA coefficients. The constant-number HOA coefficients vector is transformed to a corresponding spatial domain signal vector. In order to facilitate high-quality coding, without creating signal discontinuities the variable-number HOA coefficients vector of coefficient domain signals is adaptively normalized and multiplexed with the vector of spatial domain signals.

Abstract: There are two representations for Higher Order Ambisonics denoted HOA: spatial domain and coefficient domain. The invention generates from a coefficient domain representation a mixed spatial/coefficient domain representation, wherein the number of said HOA signals can be variable. A vector of coefficient domain signals is separated into a vector of coefficient domain signals having a constant number of HOA coefficients and a vector of coefficient domain signals having a variable number of HOA coefficients. The constant-number HOA coefficients vector is transformed to a corresponding spatial domain signal vector. In order to facilitate high-quality coding, without creating signal discontinuities the variable-number HOA coefficients vector of coefficient domain signals is adaptively normalised and multiplexed with the vector of spatial domain signals.

Abstract: When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number (?e) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalisation of the HOA data frame representation (C(k)). Then the lowest integer number of bits is set to ?e=?log2(?log2(?{square root over (KMAX)}·O)?+1)?.

Abstract: When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number (?e) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalisation of the HOA data frame representation (C(k)). Then the lowest integer number of bits is set to ?e=?log2(?log2(?{square root over (KMAX)}·O)?+1)?.

Abstract: A method for encoding multi-channel 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, 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.

Abstract: A method for encoding multi-channel 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, 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.

Abstract: A method for compressing a HOA signal being an input HOA representation with input time frames (C(k)) of HOA coefficient sequences comprises spatial HOA encoding of the input time frames and subsequent perceptual encoding and source encoding. Each input time frame is decomposed (802) into a frame of predominant sound signals (XPS(k?1)) and a frame of an ambient HOA component ({tilde over (C)}AMB (k?1)). The ambient HOA component ({tilde over (C)}AMB (k?1)) comprises, in a layered mode, first HOA coefficient sequences of the input HOA representation (cn(k?1)) in lower positions and second HOA coefficient sequences (cAMB,n(k?1)) in remaining higher positions. The second HOA coefficient sequences are part of an HOA representation of a residual between the input HOA representation and the HOA representation of the predominant sound signals.

Abstract: Higher Order Ambisonics represents three-dimensional sound independent of a specific loudspeaker set-up. However, transmission of an HOA representation results in a very high bit rate. Therefore compression with a fixed number of channels is used, in which directional and ambient signal components are processed differently. The ambient HOA component is represented by a minimum number of HOA coefficient sequences. The remaining channels contain either directional signals or additional coefficient sequences of the ambient HOA component, depending on what will result in optimum perceptual quality. This processing can change on a frame-by-frame basis.

Abstract: Encoding of Higher Order Ambisonics (HOA) signals commonly results in high data rates.

Abstract: Encoding of Higher Order Ambisonics (HOA) signals commonly results in high data rates. A method for low bit-rate encoding frames of an input HOA signal having coefficient sequences comprises computing (s110) a truncated HOA representation (CT(k)), determining (s111) active coefficient sequences (IC,ACTT(k)), estimating (s16) candidate directions (MDIR(k)), dividing (s15) the input HOA signal into a plurality of frequency subbands (f1, . . . , fF), estimating (s161) for each of the frequency subbands a subset of candidate directions (MDIR(k)) as active directions (MDIR(k,f1), . . . , MDIR(k,fF)) and for each active direction a trajectory, computing (s17) for each frequency subband directional subband signals from the coefficient sequences of the frequency subband according to the active directions, calculating (s18) for each frequency subband a prediction matrix (A(k,f1), . . .

Abstract: When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number {? e) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalisation of the HOA data frame representation (C(k)). Then the lowest integer number of bits is set to (AA).

Abstract: When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number (?e) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalization of the HOA data frame representation (C(k)). Then the lowest integer number of bits is set to (AA).

Abstract: Encoding of Higher Order Ambisonics (HOA) signals commonly results in high data rates. A method for low bit-rate encoding frames of an input HOA signal having coefficient sequences comprises computing (s110) a truncated HOA representation (CT(k)), determining (s111) active coefficient sequences (Ic,Act(k)), estimating (s16) candidate directions (MDIR(k)), dividing (s15) the input HOA signal into a plurality of frequency subbands (f1, . . . , fF), estimating (s161) for each of the frequency subbands a subset of candidate directions (MDIR(k)) as active directions (MDIR(k,f1), . . . , MDIR(k,fF)) and for each active direction a trajectory, computing (s17) for each frequency subband directional subband signals from the coefficient sequences of the frequency subband according to the active directions, calculating (s18) for each frequency subband a prediction matrix (A(k,f1), . . .