JP3134383B2 - Method and apparatus for highly efficient encoding of digital data - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a high-efficiency encoding of digital data in which input digital data is encoded by so-called high-efficiency encoding, transmitted or recorded / reproduced, and decoded to obtain a reproduced signal. The present invention relates to a method and an apparatus.

[0002]

2. Description of the Related Art There are various methods for high-efficiency encoding of signals such as audio or voice. For example, an audio signal or the like on a time axis is divided into a plurality of frequency bands by a filter without being blocked. Band division coding (sub-band coding)
Coding: SBC) and the like.
A block frequency band division method in which a signal on the time axis is converted into a signal on the frequency axis (orthogonal transformation), divided into a plurality of frequency bands, and encoding is performed for each band, so-called transform coding. Can be.

Further, a high-efficiency coding method combining the above-described band division coding and transform coding has been considered. In this case, for example, after performing band division by the above-mentioned band division coding, , And orthogonally transforms the signal of each band into a signal on the frequency axis, and encodes each of the orthogonally transformed bands.

Here, as a filter for the above-mentioned band division, there is, for example, a QMF filter.
Crochiere, Digital coding of speech in subbands, B
ellSyst.Tech. J. Vol. 55, No. 8 1976. ICASSP 83, BOSTON Polyphase Quadrature fil
ters-A new subband coding technique, Joseph H. Roth
Weiler describes an equal bandwidth filter partitioning technique. Next, as the above-mentioned orthogonal transform, for example, an input audio signal is divided into blocks in a predetermined unit time (frame), and a fast Fourier transform (FFT), a discrete cosine transform (DCT), a modified DCT transform (MDCT) is performed for each block. Or the like to convert the time axis to the frequency axis. ICA for MDCT
SSP 1987 Subband / Transform Coding Using Filter Ba
nk Designs Based on Time Domain Aliasing Cancellat
ion, JPPrincen, ABBradley, Univ. of Surrey Ro
yal Melbourne Inst. of Tech.

Further, as a frequency division width for quantizing each frequency component divided into frequency bands, for example, band division is performed in consideration of human auditory characteristics. That is, an audio signal may be divided into a plurality of bands (for example, 25 bands) with a bandwidth generally called a critical band (critical band) such that the bandwidth becomes wider as the band becomes higher. When encoding data for each band at this time, predetermined bits are allocated to each band, or encoding is performed by adaptive bit allocation (bit allocation) for each band. For example, when the coefficient data obtained by the MDCT processing is encoded by the bit allocation, adaptively to the MDCT coefficient data of each band obtained by the MDCT processing of each block, Encoding is performed with the allocated number of bits.

The following two methods are known as bit allocation methods. First, IEEE Transactions of Accoustics,
Speech, and Signal Processing, vol.ASSP-25, No.4,
In August 1977, based on the magnitude of the signal for each band,
Bit allocation is performed. In this method, the quantization noise spectrum becomes flat and the noise energy becomes minimum,
The sense of noise is not optimal because the masking effect is not used for the sense of hearing.

Next, ICASSP 1980 The critical band c
oder-digital encoding of theperceptual requirem
In the ents of the auditory system, MAKransner, and MIT, a method of obtaining a required signal-to-noise ratio for each band and performing fixed bit allocation by using auditory masking is described. However, in this method, even when the characteristic is measured with a sine wave input, the characteristic value is not so good because the bit allocation is fixed.

[0008]

As described above, when bits are allocated according to the magnitude of the signal in each band and the quantization noise energy is minimized, the audible noise level is not minimized.
If a fixed bit allocation is performed for each band in consideration of the masking effect, it is difficult to obtain good signal-to-noise characteristics when a sine wave is input.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and is intended to provide a bit allocation method which is desirable from the viewpoint of hearing and which can obtain good characteristics even for isolated spectrum input such as 1 kHz sine wave input. It is an object of the present invention to provide a highly efficient encoding method and apparatus for digital data.

[0010]

According to the present invention, there is provided a method and apparatus for encoding digital data with high efficiency, wherein an input digital signal is divided into a plurality of frequency bands and a block size is adaptively changed for each frequency band. After performing the orthogonal transform, spectrum data is obtained by performing orthogonal transformation, and the bits to be used for bit allocation are determined in advance at the time of high-efficiency encoding of digital data in which bits are adaptively assigned to each band of the spectrum data. The fixed bit allocation and the allocation depending on the size of the signal in the block, wherein the fixed bit allocation pattern is selected from a plurality of fixed bit allocation patterns having different allocation patterns. By doing so, the above-mentioned problem is solved.

Further, the above-mentioned problem is solved by a digital data high-efficiency encoding apparatus which encodes digital data by the above-mentioned digital data high-efficiency encoding method and transmits or records the digital data.

In this case, it is useful to select a pattern having a smaller high-frequency bit allocation ratio as the signal size is smaller in order to perform effective allocation. In a high-efficiency code using a frequency decomposition method for further dividing a non-blocking frequency division output into a blocking frequency, it is also advantageous to select a pattern according to the magnitude of the non-blocking frequency division output. Also, by making the number of bits of the plurality of fixed bit allocation patterns the same, the hardware scale can be reduced.

[0013]

According to the present invention, even when the spectrum is dispersed like a music signal, the noise level seen from the sense of hearing can be reduced by the masking effect even when the spectrum is dispersed. Since they are collected, the signal-to-noise ratio can be increased.

[0014]

DESCRIPTION OF THE PREFERRED EMBODIMENTS An input digital signal such as an audio PCM signal is subjected to band division coding (SBC) and adaptive conversion coding (A
An embodiment in which high-efficiency coding is performed using the techniques of (TC) and adaptive bit allocation (APC-AB) will be described with reference to FIG.

In the specific high-efficiency encoding apparatus shown in FIG. 1, an input digital signal is divided into a plurality of frequency bands by a filter or the like, and orthogonal transform is performed for each frequency band. The spectrum data is adaptively assigned bits for each so-called critical band (critical band) width in consideration of human auditory characteristics, which will be described later, and is encoded. Of course, a non-blocking frequency division width by a filter or the like may be an equal division width. Further, in the embodiment of the present invention, the block size (block length) is adaptively changed according to the input signal before the orthogonal transformation, and the critical band (critical band) width is further subdivided in a critical band unit or a high band. Floating processing is performed on the converted blocks. The critical band is a frequency band divided in consideration of human auditory characteristics, and a band of a pure tone when the pure tone is masked by a narrow band noise near the frequency of the pure tone. That is. In this critical band, the higher the band, the wider the bandwidth.
The entire frequency band of 0 kHz is divided into, for example, 25 critical bands.

That is, in FIG. 1, an audio PCM signal of, for example, 0 to 20 kHz is supplied to the input terminal 10. This input signal is divided into a band of 0 to 10 kHz and a band of 10 to 20 kHz by a band division filter 11 such as a so-called QMF filter, and a signal of the band 0 to 10 kHz is similarly divided by a band division filter 12 such as a so-called QMF filter. It is divided into a 5 kHz band and a 5 kHz to 10 kHz band. 10k from band division filter 11
The signal in the 20 kHz band is represented by Mo, which is an example of an orthogonal transformation circuit.
dified Discrete Cosine Transform (MDCT) circuit 1
3 to 5 k to 10 k from the band division filter 12.
The signals in the Hz band are sent to the MDCT circuit 14, and the signals in the 0 to 5 kHz band from the band division filter 12 are sent to the MDCT circuit 15, so that the signals are subjected to MDCT processing.

Here, each of the MDCT circuits 13, 14, 15
FIG. 2 shows a specific example of the block size of FIG. In the specific example of FIG. 2, the frequency band is widened and the time resolution is increased (the block length is shortened) toward the higher frequency side. That is, a signal in the 0-5 kHz band on the low frequency side and a
For a signal in the 10 kHz band, the number of samples in one block b _L and b _M is set to, for example, 256 samples, and 10
Each length of 1/2 with respect to the k~20kHz band signal, b _H of the low and middle band side block b _L, b _M
It is divided into blocks of length BL _L / 2 and BL _M / 2. In this way, the number of orthogonal transform block samples in each band is the same. In addition, each band can be further adaptively divided into 、, １ ／, and the like, assuming that the temporal change of the signal is large.

Referring again to FIG. 1, each MDCT circuit 13,
The spectrum data or MDCT coefficient data on the frequency axis obtained by the MDCT processing in 14 and 15 is a block in which the critical band (critical band) width is further subdivided for each so-called critical band (critical band) or in a high band. The data are grouped for each and sent to the adaptive bit allocation coding circuits 16, 17 and 18.

The adaptive bit allocation coding circuits 16, 17, 1
8, each spectrum data (or MDCT coefficient data) is reproduced according to the number of bits allocated to each critical band (critical band) or to a block obtained by further subdividing the critical band (critical band) width in a high band. I try to quantize. The data encoded in this way is taken out via the output terminals 22, 24, 26. At this time, floating information indicating what kind of signal size has been normalized and bit length information indicating what bit length has been quantized are sent at the same time.

FIG. 3 shows an adaptive bit allocation encoding circuit 16,
FIG. 3 is a functional block diagram showing a specific example of internal functions of the MDCT circuits 17 and 18, and outputs of the MDCT circuits 13, 14, and 15 in FIG. And the energy for each critical band (critical band) is calculated by, for example, calculating the square root of the root mean square of each amplitude value in the band. Instead of the energy for each band, a peak value or an average value of the amplitude value may be used. FIG. 4 shows, as an output from the energy calculation circuit 303, an example of the spectrum of the sum value in a block within a critical band (critical band) or in a further subdivided critical band (critical band) width in a high band. In FIG. 4, in order to simplify the illustration, the number of the critical bands (critical bands) or the number of block bands obtained by further subdividing the width of the critical bands (critical bands) in the high band is 12 bands (B1 to B1). B
12).

The adaptive bit allocation operation will be further described with reference to FIG. The total number of bits (bit rate) that can be used for transmission or recording by expressing the MDCT coefficient is 100 Kbp
s. This is represented in FIG. 3 by 100 Kbps of total bits from block 302 indicating the total available bits. In this embodiment, 60 Kbps is used for fixed bit allocation in the fixed bit allocation circuit 305, and the remaining 40 Kbps is used for bit allocation in the bit allocation circuit 304 depending on the bark spectrum for each band. A plurality of bit allocation patterns for fixed bit allocation are prepared, and various selections can be made according to the nature of the signal. In the embodiment, there are various patterns in which the bit amount of a short time block corresponding to 100 Kbps is distributed to each frequency.

In particular, in this embodiment, a plurality of patterns having different bit allocation ratios between the middle and low frequency bands and the high frequency band are prepared. Then, the smaller the signal size, the smaller the amount assigned to the high band is selected. In this way, a loudness effect in which the sensitivity in the high frequency band decreases as the signal becomes smaller can be used. The magnitude of the signal at this time is
Although the magnitude of the signal in the entire band can be used, an output of a non-blocking frequency division circuit using a filter or the like or an MDCT output is used.

The sum calculation circuit 306 calculates the sum of the fixed bit allocation and the value of the bit allocation depending on the signal value of the block in which the critical band (critical band) width is further subdivided in the critical band (critical band) or the high band. Taken,
It is taken out via the output terminal 307 and used for quantization. Here, FIG. 5 shows a state of bit allocation when the signal spectrum is flat, and FIG. 6 shows a state of quantization noise (noise spectrum) corresponding thereto. FIG. 7 shows a state of bit allocation when the tonality of the signal spectrum is high, that is, when the signal has an auditory sense of pitch and the frequency is biased, and the corresponding quantization noise (noise spectrum) is shown. 8) is shown in FIG. Here, in FIGS. 5 and 7, the white portions indicate the bit amounts for the fixed bit allocation, and the hatched portions indicate the bit amounts for the signal level dependence. 6 and 8, a curve a indicates a signal level, a curve b indicates a noise level due to a fixed bit allocation, and a hatched portion c indicates a noise reduction due to a signal level dependence.

That is, FIGS. 5 and 6 show a case where the spectrum of a signal is relatively flat, and the noise level due to the fixed bit allocation is useful for obtaining a certain signal-to-noise ratio over the entire band. However, relatively low bit allocation is used in the low band and the high band. This is because the importance of this band is small acoustically. At the same time, the signal level-dependent bit allocation allows the noise level in a band where the signal magnitude is large to be selectively reduced. However, if the signal spectrum is relatively flat, this selectivity will also work over a relatively wide band.

On the other hand, as shown in FIGS. 7 and 8, when the signal spectrum exhibits high tonality, the reduction of the quantization noise due to the signal level-dependent bit allocation reduces the noise in an extremely narrow band. Used to reduce. This achieves an improvement in the characteristics of the isolated spectrum input signal.

FIG. 9 shows a decoding circuit for transmitting or recording / reproducing the high-efficiency-encoded signal and then decoding it again. The quantized MDCT coefficients of each band are supplied to decoding circuit input terminals 122, 12
4 and 126, and the used block size information is supplied to input terminals 123, 125 and 127. The decoding circuits 116, 117 and 118 release the bit allocation using the adaptive bit allocation information. Next, signals on the frequency axis are converted into signals on the time axis by IMDCT (inverse MDCT) circuits 113, 114, and 115. The signals on the time axis of these partial bands are output to an IQMF (inverse QMF) circuit 11.
2 and 111, the signal is decoded into a full band signal.
Take out from 10.

[0027]

According to the high-efficiency encoding method of digital data according to the present invention, after dividing an input digital signal into a plurality of frequency bands, orthogonal transform is performed, and the obtained spectrum data is adaptively applied to each band. Is a highly efficient encoding method for digital data in which bits are allocated to a predetermined fixed bit allocation and an allocation depending on the size of a signal in a block. The fixed bit allocation pattern is a plurality of fixed bit allocation patterns having different allocation patterns. This bit allocation technique is audibly desirable, and
Good characteristics can be obtained even for isolated spectrum input such as 1 kHz sine wave input, and a bit distribution obtained by only one operation can be realized without adjusting the bit amount repeatedly.
That is, even when the spectrum is dispersed like a music signal, the noise level can be reduced from the viewpoint of hearing due to the masking effect, and bits can be collected in a large band of the signal even when a sine wave is input, so that the signal-to-noise ratio can be reduced. Can be increased.

The same effect can also be obtained by high-efficiency encoding of digital data in which digital data is encoded and transmitted or recorded by the above-described high-efficiency encoding method of digital data.

[Brief description of the drawings]

FIG. 1 is a block circuit diagram illustrating a configuration example of an encoding device according to an embodiment of the present invention.

FIG. 2 is a diagram illustrating a specific example of frequency and time division of a signal of the embodiment apparatus.

FIG. 3 is a functional block diagram for explaining an example of a bit allocation algorithm of an adaptive bit allocation encoding circuit used in the embodiment device.

FIG. 4 is a diagram showing a bark spectrum.

FIG. 5 is a diagram illustrating an example of bit allocation when a signal having a substantially flat spectrum is input in the embodiment.

FIG. 6 is a diagram illustrating an example of a quantization noise spectrum when a signal having a substantially flat spectrum is input according to the embodiment.

FIG. 7 is a diagram illustrating an example of bit allocation when a signal having high tonality is input according to the embodiment.

FIG. 8 is a diagram illustrating an example of a quantization noise spectrum when a signal having high tonality is input according to the embodiment.

FIG. 9 is a block circuit diagram showing a configuration example of a decoding device for the encoding device of the embodiment.

[Explanation of symbols]

10 High efficiency coding circuit input terminal 11, 12 QMF circuit 13, 14, 15 MDCT circuit 16, 17, 18 ... Adaptive bit allocation coding circuit 19, 20, 21,. -Block size determination circuit 22, 24, 26 ... Encoding output terminal 23, 25, 27 ... Block size information output terminal 122, 124, 126 ... Encoding input terminal 123, 125, 127 ... Block size information input terminals 116, 117, 118 ... adaptive bit allocation decoding circuits 113, 114, 115 ... IMDCT circuits 112, 111 ... IQMF circuits 110 ... high efficiency decoding circuit output terminals 300 .. Adaptive bit allocation function section 302: block indicating total number of usable bits 303: energy calculation circuit for each band 304: energy Lugi-dependent bit distribution circuit 305: fixed bit distribution circuit 306: bit sum operation circuit

──────────────────────────────────────────────────続 き Continued on the front page (58) Field surveyed (Int.Cl. ⁷ , DB name) H03M 7/30

Claims (4)

(57) [Claims] 1. An input digital signal is divided into a plurality of frequency bands, and after a block size is adaptively changed for each frequency band, spectrum data is obtained by performing an orthogonal transform. A high-efficiency encoding method for digital data in which bits are adaptively allocated for each of the bits, wherein bits used for bit allocation are predetermined fixed bit allocations and bit allocations depending on the size of signals in a block. The high efficiency encoding method for digital data, wherein the fixed bit allocation pattern is selected from a plurality of fixed bit allocation patterns having different allocation patterns. 2. The digital data according to claim 1, wherein the fixed bit allocation pattern selects a fixed bit allocation pattern with less bit allocation to a high frequency band according to the size of a signal in a band. High efficiency encoding method. 3. The fixed bit allocation pattern according to claim 1, wherein the fixed bit allocation pattern is selected according to the size of the non-blocking frequency division output by a frequency division method of further dividing the non-blocking frequency division output into a blocking frequency. Item 2. The method for highly efficient encoding of digital data according to Item 1. 4. An input digital signal is divided into a plurality of frequency bands, and a block size is adaptively changed for each frequency band. Then, orthogonal transform is performed to obtain spectrum data. A digital data high-efficiency encoding device that adaptively allocates bits for each bit, wherein bits used for bit allocation are predetermined fixed bit allocations and allocations depending on signal sizes in blocks. And a means for allocating the fixed bit allocation pattern to a plurality of fixed bit allocation patterns having different allocation patterns.