Efficient coding of high frequency signal information in a signal using a linear/non-linear prediction model based on a low pass baseband
View Patent ↗An efficient coding scheme with higher audio bandwidth and/or better audio quality at lower bitrates, wherein the scheme eliminates long-term and short-term frequency domain correlation in a signal via frequency domain predictors. The coding scheme compresses information consisting of coded low frequency components as well as a parametric representation for the high frequency components based on a non-linear model. Additionally, by working on the frequency domain representations of the signal (such as the MDCT representation which is naturally available to a PAC encoder and decoder), low pass and high pass signal components are easily obtained by windowing the appropriate ranges of frequencies in the signal. Furthermore, the power functions of the signal are replaced by corresponding convolution functions of the same order.
1. A system for efficiently coding signal information via predictors, said system comprising:
a) a high-pass filter extracting high-frequency components of said signal;
b) a low-pass filter extracting low-frequency components of said signal;
c) linear and non-linear predictors used in modeling a parametric representation of said high frequency components of said signal, said high frequency component modeled as:
X
HFC
(
f
)
=
∑
i
=
1
N
β
i
X
′
LFC
(
f
-
M
-
i
)
+
R
HFC
(
f
)
,
wherein, in case of said linear predictor,
X′ LFC ( f )= X LFC ( f )
and in case of said non-linear predictor,
X
LFC
(
f
)
=
∑
i
=
1
N
(
X
LFC
(
f
)
*
X
LFC
(
f
)
*
…
*
X
LFC
(
f
)
)
j
,
and
d) an encoder encoding said extracted low-frequency components and parameters associated with said linear and non-linear predictors.
2. A system as per claim 1 , wherein said system further comprises a quantizer for quantizing said reconstruction estimate R HFC (f) based upon one or more codebooks.
3. A system as per claim 2 , wherein said codebook is a gain-shape random codebook.
4. A system as per claim 1 , wherein N is obtained by estimating the minimum approximation error over a small range of N and then choosing N for which optimal approximation error is minimized.
5. A system as per claim 1 , wherein said high and low frequency components are obtained via windowing an appropriate range of frequencies in said signal.
6. A system as per claim 1 , wherein said encoder is a perceptual audio encoder.
7. A system as per claim 1 , wherein an encoding algorithm associated with said encoder is adaptively chosen from one or more encoding algorithms based upon which of said algorithms provides the best compression ratio.
8. A system as per claim 7 , wherein a processing state identifying said adaptively chosen encoding algorithm is transmitted as a part of said encoded output signal via a bitstream header.
9. A system as per claim 7 , wherein said encoder adaptively chooses any of the following features for efficient high frequency coding: lattice quantization of scale factors, multidimensional coding of peaks, or frequency range.
10. A system for efficiently coding signal information, said system comprising:
a) a high-pass filter extracting high-frequency components of said signal;
b) a low-pass filter extracting low-frequency components of said signal;
c) predictors for eliminating interharmonic frequency correlation in said signal by modeling said high frequency components of said signal via linear predictors;
d) non-linear predictors for modeling said high frequency components of said signal via a parametric representation using a non-linear predictor model; and
e) an encoder encoding said extracted low-frequency components and parameters associated with said linear predictors.
11. A system as per claim 10 , wherein said non-linear predictor model is given by:
X
HFC
(
f
)
=
∑
i
=
1
N
β
i
X
′
LFC
(
f
-
M
-
i
)
+
R
HFC
(
f
)
,
wherein
X
HFC
(
f
)
=
∑
i
=
1
N
β
i
X
LFC
′
(
f
-
M
-
i
)
+
R
HFC
(
f
)
,
and said encoder further encoding parameters associated with said non-linear predictors.
12. A system as per claim 11 , wherein said system further comprises a quantizer for quantizing said reconstruction estimate R HFC (f) based upon one or more codebooks.
13. A system as per claim 12 , wherein said codebook is a gain-shape random codebook.
14. A system as per claim 10 , wherein N is obtained by estimating the minimum approximation error over a small range of N and then choosing N for which optimal approximation error is minimized.
15. A system as per claim 10 , wherein said high and low frequency components are obtained via windowing an appropriate range of frequencies in said signal.
16. A system as per claim 10 , wherein said encoder is a perceptual audio encoder.
17. A system as per claim 10 , wherein said encoder utilizes an encoding algorithm, and wherein said encoding algorithm is adaptively chosen from one or more encoding algorithms based upon which of said algorithms provides the best compression ratio.
18. A system as per claim 17 , wherein a processing state identifying said adaptively chosen encoding algorithm is transmitted as a part of said encoded output signal via a bitstream header.
19. A system as per claim 17 , wherein said encoder adaptively chooses any of the following features for efficient high frequency coding: lattice quantization of scale factors, multidimensional coding of peaks, or frequency range.
20. A system per claim 10 , wherein said high frequency component is modeled as:
X
LFC
(
f
)
=
∑
j
=
1
N
(
X
LFC
(
f
)
*
X
LFC
(
f
)
*
…
*
X
LFC
(
f
)
)
j
,
21. A method for efficiently coding signal information, said method comprising the steps of:
a) extracting high-frequency components of said signal;
b) extracting low-frequency components of said signal;
c) modeling a parametric representation of said high frequency components of said signal with linear and non-linear predictors, said high frequency component modeled as:
X
HFC
(
f
)
=
∑
i
=
1
N
β
i
X
′
LFC
(
f
-
M
-
i
)
+
R
HFC
(
f
)
,
wherein, in case of said linear predictor,
X′ LFC ( f )= X LFC ( f )
and in case of said non-linear predictor,
X
LFC
′
(
f
)
=
∑
j
=
1
N
(
X
LFC
(
f
)
*
X
LFC
(
f
)
*
…
*
X
LFC
(
f
)
)
j
,
and
d) encoding said extracted low-frequency components and parameters associated with said linear and non-linear predictors.
22. A method as per claim 21 , wherein N is obtained by estimating the minimum approximation error over a small range of N and then choosing N for which optimal approximation error is minimized.
23. A method as per claim 21 , wherein said high and low frequency components are obtained via windowing an appropriate range of frequencies in said signal.
24. A method as per claim 21 , wherein said encoding is done via a perceptual audio encoder.
25. A method as per claim 21 , wherein said method further comprises the step of adaptively choosing an encoding algorithm from one or more encoding algorithms based upon which of said algorithms provides the best compression ratio.
26. A method as per claim 25 , wherein said method further comprises the step of transmitting a processing state identifying said adaptively chosen encoding algorithm is transmitted as a part of said encoded output signal via a bitstream header.
27. An article of manufacture comprising a computer usable medium having computer readable program code embodied therein for efficiently coding signal information, said medium comprising:
a) computer readable program code extracting high-frequency components of said signal;
b) computer readable program code extracting low-frequency components of said signal;
c) computer readable program code modeling a parametric representation of said high frequency components of said signal with linear and non-linear predictors, said high frequency component modeled as:
X
HFC
(
f
)
=
∑
i
=
1
N
β
i
X
LFC
′
(
f
-
M
-
i
)
+
R
HFC
(
f
)
,
wherein, in case of said linear predictor,
X′ LFC ( f )= X LFC ( f )
and in case of said non-linear predictor,
X
LFC
(
f
)
=
∑
j
=
1
N
(
X
LFC
(
f
)
*
X
LFC
(
f
)
*
…
*
X
LFC
(
f
)
)
j
,
and
d) computer readable program code encoding said extracted low-frequency components and parameters associated with said linear and non-linear predictors.
28. The article of manufacture as per claim 27 , wherein N is obtained by estimating the minimum approximation error over a small range of N and then choosing N for which optimal approximation error is minimized.
29. The article of manufacture as per claim 27 , wherein said high and low frequency components are obtained via windowing an appropriate range of frequencies in said signal.
30. The article of manufacture as per claim 27 , wherein said encoding is done via a perceptual audio encoder.
31. The article of manufacture as per claim 27 , wherein said article further comprises computer readable program code for adaptively choosing an encoding algorithm from one or more encoding algorithms based upon which of said algorithms provides the best compression ratio.
32. The article of manufacture as per claim 31 , wherein said article further comprises computer readable program code for transmitting a processing state identifying said adaptively chosen encoding algorithm transmitted as a part of said encoded output signal via a bitstream header.