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WO1994018762A1 - Transmission de mots contenant des donnees numeriques representant une forme d'onde de signal - Google Patents

Transmission de mots contenant des donnees numeriques representant une forme d'onde de signal Download PDF

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WO1994018762A1
WO1994018762A1 PCT/GB1994/000297 GB9400297W WO9418762A1 WO 1994018762 A1 WO1994018762 A1 WO 1994018762A1 GB 9400297 W GB9400297 W GB 9400297W WO 9418762 A1 WO9418762 A1 WO 9418762A1
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data
digital
waveform
audio
signal
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Michael Anthony Gerzon
Peter Graham Craven
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    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11B—INFORMATION STORAGE BASED ON RELATIVE MOVEMENT BETWEEN RECORD CARRIER AND TRANSDUCER
    • G11B20/00—Signal processing not specific to the method of recording or reproducing; Circuits therefor
    • G11B20/10—Digital recording or reproducing
    • G11B20/10527—Audio or video recording; Data buffering arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/66—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission for reducing bandwidth of signals; for improving efficiency of transmission
    • H04B1/665—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission for reducing bandwidth of signals; for improving efficiency of transmission using psychoacoustic properties of the ear, e.g. masking effect
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B14/00—Transmission systems not characterised by the medium used for transmission
    • H04B14/02—Transmission systems not characterised by the medium used for transmission characterised by the use of pulse modulation
    • H04B14/04—Transmission systems not characterised by the medium used for transmission characterised by the use of pulse modulation using pulse code modulation
    • H04B14/046—Systems or methods for reducing noise or bandwidth

Definitions

  • This invention relates to methods and apparatus for transmitting, encoding and decoding data signals using parts of low significance of the digital words representing signal waveforms, particularly in applications where the degradation of the waveform signal resulting from the data coding is desired to be of minimal or benign effect.
  • a signal waveform is represented by a sequence of digital words
  • the accuracy of the digital word is greater than is strictly required for a satisfactory representation of the original waveform
  • audio signal waveforms are represented by 16-bit wordlength data sampled at 44.1 kHz, and by use of techniques such as dither and noiseshaping described in references [1] - [4] and [16] - [19] , this wordlength is capable of producing a perceived dynamic range exceeding 110 dB, whereas existing technologies and consumer requirements rarely require perceived dynamic ranges of more than 90 or 100 dB.
  • professional digital video standards often use 10 bit words to represent video signal waveforms, which has a significant quality margin above the quality found acceptable to most viewers.
  • This prior-art sub-band method has many disadvantages. Firstly, the process of both encoding and decoding is a complicated one requiring a high level of signal processing complexity. Secondly, there is an inherent time delay in the signal processing involved in splitting signals into subbands. Thirdly, the data rate that can be encoded by the sub-band method is reduced for small input waveform to a low level.
  • a particular disadvantage of the sub-band method is that it relies on models of auditory masking perceptually to hide the error caused by data coding in the signal waveform words, coding the data at levels within particular sub ⁇ bands that are determined adaptively by a model for auditory masking to be masked by the audio signal.
  • Such masking models are still imperfect, and moreover, masking thresholds are not deterministic but probabilistic in nature, so that there is a finite probability of error signals below a masking threshold being detected by the ears.
  • the waveform degradations produced by the sub- band method will in general produce audible effects that may not be acceptable for the highest quality uses.
  • a further disadvantage of the sub-band method is that in practice it is not efficient in an information-theoretic sense.
  • the invention allows coding of data within the digital words representing signal waveforms such that the coding is efficient in the sense of information theory, thereby minimising added error noise levels, involves only short or zero time delays in the signal processing, and in which nonlinear distortion and data-related error variation effects are avoided, and also allows if desired avoidance of all modulation noise effects as well.
  • the invention also allows the spectral characteristics of the error noise to be modified so as to minimise its perceptual level, which in general depends on the spectral characteristics.
  • a method of encoding digital data within digital words representing signal waveforms including the step of modifying least significant digits of said digital words representing signal waveforms in dependence upon said digital data, characterised by pseudo-randomising said digital data thereby forming data noise words having levels small relative to those of said waveform words, subtracting the pseudo-randomised data words from said waveform, words thereby producing a dithered. aveform word, and quantizing said dithered waveform word and adding said data noise word to said quantized word thereby forming an output of reduced noise carrying information representing digital data in the least significant digits thereof.
  • the method may be implemented using " : means of receiving input digital waveform words representing input waveform signals, means of receiving input data information, means for outputting output digital waveform words representing an output waveform signal and incorporating data information, means for pseudo-randomising said data information and for forming it into a word signal termed the data noise signal having a level or range of levels small relative to that of the waveform words, means for subtracting said data noise signal from digital words representing said input waveform producing dithered waveform words, means for uniformly quantizing said dithered waveform words, and means for adding said data noise signal to the output of said uniform quantizing means to produce output digital words, wherein least significant digits of the digital words representing signal waveforms are replaced in the output digital words by information representing said data information in a pseudo-randomised form.
  • the least significant digits of a digital word may be the digits in a binary representation of the word, or the least significant digits in representations of the word in any other integer base or bases.
  • noise shaping means around said uniform quantizing means adapted to modify the spectrum of the difference between output and input waveform signals in a desired predetermined manner.
  • said uniform quantizer means may be a uniform vector quantizer for a plurality n of signal channels in the sense defined below, and said data noise signal may be a vector noise signal in said plurality n of signal channels.
  • the difference between output and input waveform signals has the form of a noise signal substantially free of nonlinear distortion products related to the input waveform signal, because the data noise signal has a probability distribution function adapted to subtractively dither the uniform quantizer with substantially no resulting nonlinear distortion.
  • a means for decoding data information encoded int the least significant digits of digital waveform wor representing waveform signals comprising means for receiving said digital waveform words, means of separating said least significant digit from said digital waveform words, means for inverting pseudo-random encoding in sai least significant digits to provide data information and means of outputting said data information.
  • a system for encoding and decoding dat information within the least significant digits of digita waveform words representing waveform signals comprising encoding means according to the above first aspect, decoding means according to the above second aspect, and transmission means for conveying the output of sai encoding means to the input of said decoding means.
  • the said transmission means may, by way of example, be wire or optical link, or a link using radio, acoustic o infra red waves, or may be via a storage medium such a memory storage media, hard disc media, magnetic tape o optical disc recording, storage and playback media or an sequential combination of these.
  • the inventio When applied to audio CD (compact disc) , the inventio provides a new method for burying a high data rate dat channel (with up to 360 kbit/s or more) compatibly withi the data stream of an audio CD without significan impairment of existing CD performance.
  • a proposal in thi description is to replace a number (typically up to fou per channel) of the least significant bits (LSBs) of th audio words by other data, and to use the psychoacousti noise shaping techniques associated with noise shape subtractive dither to reduce the audibility of the resulting added noise down to a subjective perceived level equal to that of conventional CD.
  • LSBs least significant bits
  • the wordlength of existing signals would be truncated to (say) only 12 bits, which would not only reduce the basic quantization resolution by 24 dB, but also would introduce the problems of added distortion and modulation noise caused by truncation (e.g. see refs. [1-4]) .
  • the replaced last (say) 4 LSBs would themselves constitute an added noise signal, which itself may not have a perceptually desirable random-noise like quality, and will also add to the perceived noise level in the main audio signal, typically increasing the noise by a further 3 dB above that due to truncation alone, giving in this case as much as 27 dB degradation total in noise performance.
  • the invention incorporates methods of overcoming all these problems in replacing the last few LSBs of an audio signal by other data.
  • the new method involves the following preferred steps:
  • this pseudo-random data signal as a subtractive dither signal (e.g. see [1-4]), so that simultaneously it does not add to the perceived noise and that it removes all nonlinear distortion and modulation noise effects caused by truncation.
  • this does not require the use of a special subtractive dither decoder, so that the process works on a standard off-the-shelf CD player, and
  • C) preferably additionally, at the encoding stage, incorporating psychoacoustically optimized noise shaping of the (subtractive) truncation error, thereby reducing the perceived truncation noise error by around 17 dB further.
  • the overall effect of combining these three processes is that if one incorporates data into the last few LSBs, then the effects of distortion, modulation noise and perceived audible patterns in the LSB data are completely removed, and the resulting perceived steady noise is reduced by around 23 dB below that of ordinary unshaped optimally dithered quantization to the same number of bits.
  • the perceived S/N signal- to-noise ratio
  • the noise-shaping can also be varied adaptively at the encoding stage so that at high audio levels, the noise error is maximally masked by the audio signal, thereby increasing the data rate of the buried channel during loud passages to, in some cases, as much as 700 kbit/s.
  • the approach in this invention is substantially different from an alternative method of burying data described in [5] , which involved a process of splitting the audio signal into subbands, replacing the LSBs of the subbands with data based on auditory masking theory, and then reassembling the resulting data by recombining the subbands.
  • process very complicated, with a considerable time- delay penalty in the subband encoding/decoding process, but it has to be done with extraordinary precision to prevent data errors in the band splitting and recombining process.
  • the present process involves little time delay, involves relatively simple signal processing, and further is such as to guarantee the lack of audible side- effects due to nonlinear distortion, modulation noise or data-related audible patterns.
  • a buried data channel particularly with an audio CD is to transmit alternative mixes of sound to that conveyed in the main channels.
  • a data-reduced audio signal may be conveyed using the buried data channel to convey an alternative sound mix of a piece of music particularly suited for special listening conditions, such as radio air play or use in exceptionally noisy environments such as in-car or background music use.
  • a further extension of such uses is in Library music, where functional music for use as backgrounds in radio, film, advertising, multi-media, audio visual or television productions is put onto CD.
  • Library music essentially only one mix can be conveyed on a track of a CD, but by incorporating in the buried data channels, additional data - compressed mixes or submixes in synchronism with the main channels, alternative mixes can be created by mixing together information from the main and buried data audio channels.
  • the main stereo channels may contain a pre-determined mix a-iA+b- j B+c- j C for mixing coefficients a-,, b-,, c, for general use, and the data compressed channels may convey two further mixes a j A+b j B+C j C and a j A+b j B+C j C for mixing coefficients a 2 , b 2 , c 2 and a 3 , b 3 , c 3 .
  • A, B and C may be recovered to obtain any desired mix (a ⁇ A+b 0 B+c 0 C) of A, B and C. This technically may be done by putting them in the 3 x 3 matrix.
  • This mix down method can be used also for consumer music releases where it is desired to give to the public the ability to produce modified mixes other than the standard mix of the main audio stereo channels.
  • One application of this ability to provide alternative mixes is the possibility of providing a choice of languages for vocals in a music release aimed at a multi-lingual market, with the main channels conveying one language, and the subsidiary channels conveying, for example the difference between the vocals in the first and in a second language. Subtracting this "difference" vocal channel from the main channels will produce a track with vocals in the second language, while still retaining the full quality of the main channel for all the backing musical lines.
  • One application of the new data channel is using the additional bits to add, using audio data compression, additional audio channels for three- or more-speaker frontal stereo or surround sound as shown in Figure 16, such as described for example in [6] , [7] , [8] .
  • additional audio channels for three- or more-speaker frontal stereo or surround sound as shown in Figure 16, such as described for example in [6] , [7] , [8] .
  • the data rate available is sufficient to transmit a Dolby AC-3 or MUSICAM surround 5-channel surround-sound signal, but these systems involve a quality compromise with the data rate, so that this is not a preferred procedure.
  • High-quality data compressed additional audio channels can, unlike existing data compression systems, minimize the risk of destruction of subtle auditory cues such as those for perceived distance, thereby maintaining CD digital audio as the preferred medium for high quality audio, while adding additional channels.
  • additional buried audio channels either for frontal-stage 3- or 4- speaker stereo or for 3-channel horizontal or 4-channel full-sphere with height [13] ambisonic surround sound (see refs.
  • the buried data channel can be used for conveying related computer data, such as graphics, data files, computer games, multilingual text or track copyright information and a data rate of 350 kbit/s is even enough to convey a reasonable video image by using a video data reduction system such as MPEG.
  • related computer data such as graphics, data files, computer games, multilingual text or track copyright information
  • a data rate of 350 kbit/s is even enough to convey a reasonable video image by using a video data reduction system such as MPEG.
  • Another use would be to convey dynamic-range reduction or enhancement data, e.g. a channel conveying the setting of a gain moment by moment.
  • This would allow the same CD automatically to be played with different degrees of dynamic compression according to environment, by choosing the gain adjustment channel appropriate to that environment. This would include the possibility of completely uncompressed quality for high-quality use.
  • the present proposal differs in that the buried data channel is used to convey a signal representing the actual gain to which the audio waveform signal is to be subjected to moment by moment.
  • the gain need not be rigidly specified by any particular design of compressor or expander, but may be chosen freely from that derived by many different kinds of compressors or expanders, or even derived from manual gain adjustment by an artistically skilled operative.
  • the gain signal may be conveyed by any known method. For example, it might by conveyed using say 12 successive bits in a data signal to convey using PCM the value of the gain control signal to 12 bit resolution with a bandwidth limited to the Nyquist resolution of the sample rate of the 12 bit words.
  • the gain waveform will be coded in the data stream using Differential PCM techniqes rather than PCM techniques, since this will generally convey the gain control signal with a higher resolution at a given data rate.
  • Well-known techniques of efficient data transmission such as Huffman coding may be used to maximise the gain control signal resolution within the available data rate.
  • the decoder will recover the buried data as described in the following, will recover from this, by DPCM and Huffman decoding as appropriate, the original gain control signal, and will then alter the gain of the main audio channels by multiplying these channels by the value of the gain control signal as shown schematically in Figure 17.
  • MIDI Musical Instrument Digital Interface
  • Other continuous control signals can be conveyed digitally by the buried data channel in a similar manner, for example by transmitting the data in one or more channels of MIDI (Musical Instrument Digital Interface) control information.
  • MIDI control signals can be used to adjust the reporduciton parameters of the main audio channels by means of MIDI controlled gains, panpots and equalisers, reverberation units and similar effects devices in order to produce desired alterations for special reproduction purposes.
  • Such MIDI or similar control signals in the buried data channel can additionally or instead be used to cause the performance of MIDI-controlled synthesiser sound modules for the purposes of adding additional musical lines to those conveyed in the main audio waveform of the CD.
  • FIG. 18 A further use related to the original audio is shown schematically in Figure 18 and is to add in the subchannel data-reduced information allowing information above 20 kHz to be reconstructed. It is widely noted that there is a significant loss of perceived quality cuased by the sharp bandlimiting to 20kHz when comparing high-quality digital signals sampled at say 44.1 kHz as compared to 88.2 kHz.
  • the extended bandwidth can be provided, for example, by using a high-order complementary mirror filter pair of the kind described in Regalia et al. [20] and in Crochiere and Rabiner [21] to split an 88.2 kHz-rate sampled digital signal into two bands sampled at 44.1 kHz.
  • the filters involved will overlap, although using a high-order filter [20] , the region of significant overlap can be reduced to of the order of a kHz. Within the overlap region there will be aliasing from the other frequency range, although the reconstruction of the full bandwidth [20,21] will cancel out this aliasing.
  • the band below 22.05 kHz can then be transmitted as the conventional audio, and the band above 22.05 kHz can be transmitted in data reduced form in the buried data channel at a reduced data rate of, say, between 1 and 4 bits per sample per channel, using known sub-band or predictive coding methods.
  • This arrangement is illustrated in Figure 18.
  • Phase compensation inverse to the phase response of the low pass filter in the complementary filter pair may be employed to linearise the phase response of the main sub-22.05 kHz signal for improved results for standard listeners, with the use of an inverse phase compensating filter in the decoding process for reconstructing the wider bandwidth signal.
  • the potential quality problem caused by aliasing within the main audio waveform may be avoided by conveying a lower frequency range via a low pass filter that has substantially zero response above 22.05 kHz, and a higher frequency range in data-reduced form that includes some overlap of frequency range with the band below 22.05 kHz.
  • the buried data channel could be used for example to convey one additional audio channel, a dynamic range gain signal, extended bandwidth and additional graphics, text (possibly in several languages) , copyright and even insert video data as appropriate.
  • the invention may be used to convey other data in the least significant digits of the waveform data, while minimally affecting the noise performance in the waveform data.
  • Figure 1 shows pseudo random encoding and decoding of data transmitted via a digital channel to ensure noise-like behavior.
  • Figure 2 shows a binary pseudo-random sequence generator using shift-register logic, with input "exclusive or” gate for encoding and decoding of a binary data stream.
  • Figure 3 shows a schematic of processing of data to form an audio noise-like signal.
  • Figure 4 shows subtractive dither around a uniform quantizer.
  • Figure 5 shows subtractive dither using a combination of discrete and continuous RPDF dither.
  • Figure 6 shows a noise shaped subtractively dithered uniform quantizer.
  • Figures 8a and 8b show noise shaping round pseudo random data noise signal encoding of data into an audio word using the standard noise shaper form and round a modified process.
  • Figure 10 shows a further implementation of noise shaping round pseudo random data noise signal encoding of data into an audio word.
  • Figure 11 shows the recovery of the data signal from the received coded audio word.
  • Figure 12 shows the 2-dimensional rhombic quantizer region (shaded square with sides tilted 45°) shown against a background (squares with horizontal and vertical sides) of conventional independent quantizers (whose square quantizer region is darkly shaded) on each channel y-, and
  • Figure 13 shows the use of extra subtractive dither to eliminate nonlinear distortion and modulation noise at LSB level, using noise shaped triangular PDF dither having ⁇ 1 LSB peaks to achieve good results in both nonsubtractive reproduction of output audio word and (shown) subtractive reproduction.
  • Figures 14 and 15 show the use of autodither to generate triangular dither in the encoder and audio decoder.
  • Figure 16 shows the encoding of three or more audio channels as a pair of normal audio channels on CD with the remaining information conveyed using audio data compression in the least significant digits, and the recovery of these channels and their mixing or combining to form output audio channels, either for mixdown use or for multi-channel directional sound reproduction.
  • Figure 17 shows the encoding and the decoding as least significant bit buried data a signal intended for optional gain alteration of the reproduced CD sound.
  • Figure 18 shows the encoding and the decoding of information coded in data-reduced form in the least significant bits for the increase of audio bandwidth beyond the 20 kHz limits of conventional CD.
  • a signal processing circuit for encoding data within a digitised signal waveform comprises a pseudo-random encoder 1 and a uniform quantizer 2.
  • the pseudo-random encoder applies a reversible pseudo-random function to the input data so that the output is noise-like.
  • the output from the pseudo-random encoder 1 is substracted from an input digital word representing a signal waveform. After subtraction, the modified waveform word is quantized by the quantizer which in this example has a uniform quantization characteristic.
  • a noise-shaping loop is provided around the quantizer 2 and the data noise subtraction node.
  • This circuit, and the alternative circuits dicsussed below, are conveniently implemented by means of signal processing algorithms programmed and implemented in ways well known to those skilled in the art on.
  • general, purpose, digital signal processing chips such as those in the Motorola DSP 56000 family such as the DSP56001 or DSP56002, or chips of the Texas Instrument TMS320 family, although any digital signal processing hardware capable of performing the required arithmetic and logic operations may be used, including programmable logic chips and arithmetic logic units and general purpose central processors used in computers.
  • the data encoding algorithms are implemented as programs stored in program memory, operating on a time series of digital input words representing waveform signals and on data signals, and providing a time series of digital output signal words representing modified waveform words incorporating data signal information.
  • the data decoding algorithms are implemented as programs stored in program memory, operating on a time series of digital input words representing waveform signals incorporating data signals, and providing an output data signal information.
  • the digital waveform signal being processed will usually have been derived either by passage through an analogue-to- digital converter from analogue waveform signals, or from signals directly synthesised in the digital domain.
  • the output waveform words may be converted to analogue waveforms by use of a digital to analogue converter.
  • the data signal is a data-reduced signal for analogue waveforms, such as data-compressed audio or image video signals, any available hardware or software method may be used to encode the extra waveform information into a data-reduced form, and to decode the recovered buried data signal back into a waveform signal.
  • fig.2 shows a well-known binary pseudo-random logic sequence generator using feedback around three logic elements and a total shift register delay of 16 samples (a 1-sample delay is denoted by the usual notation z '1 ) .
  • the pseudo-random sequence generator of fig. 2 is fed with a binary data stream s n , then it has the effect of a pseudo-randomizer for the input data.
  • pseudo-random binary sequence logic generators with shift registers of longer length L than 16 samples can be used for encoding and decoding in the same way, with their fed-back output given by subjecting the delayed sequence output and the input to a "sum" logic gate.
  • Such length L sequences will have, for a constant input, only one chance in 2 -1 of giving an unrandomised output, and will have a sequence length of 2 -1 samples.
  • the pseudorandom binary sequence generator described in (2-1) and fig. 2 is a maximum length sequence for a zero input, it has a shorter length for an all-one constant input, and in general, the precise behavior with, say periodic inputs is hard to predict. Partly for this reason, it is not absolutely essential to use a maximum- length sequence generator, provided that the length of the sequence is not too short for constant inputs.
  • the data will first be arranged to form a number of bits of data per sample of each audio channel, for example 8 bits of data constituting bits 12 to 15 of the left and the right audio channels (where bit 0 is the most significant bit (MSB) of a 16 bit audio word and bit 15 the least significant bit) .
  • MSB most significant bit
  • each of these (say 8) bits will, separately, be encoded by a pseudo-random logic such as that of fig. 2 to form a pseudo random sequence, and the resulting pseudo- randomized bits used to replace the original bits in (say) bits 12 to 15 of the left and the right audio channels.
  • the resulting noise signals in the left and right audio channels will be termed the (left and right) data noise signals.
  • pseudo-randomizing individual bits of the audio words representing data separately they can be pseudo-randomized jointly by regarding the successive data bits of a word as being ordered sequentially in time, and applying a pseudo-random encoder such as that of figure 2 to this sequence of bits. For example, eight bits of data per audio sample can be sequentially ordered before the next eight bits of data corresponding to the next audio sample, and the pseudo random-logic encoding can be applied to this time series of bits at eight times the audio sampling rate.
  • An advantage of this strategy is that errors in received audio samples propagate for (in this example) for only one eighth of the time as in the case where each word bit is separately pseudo-randomized.
  • M-level data signals taking one of M possible values, conveying log ⁇ bits per sample can also be pseudo- randomized by a direct process involving congruence techniques, whereby the coded version w' n of the current sample M-level word w n is given by
  • the congruence technique can result in sequence lengths for constant inputs of length up to a maximum of M L -1 samples, so that in general, the larger the value of M, the smaller need be L, with a consequent shortening of the time duration of propagation of errors.
  • a slightly more complex pseudo-randomization of data will provide an initial pseudo-randomization of M-level data by a method such one of those described here, and follow it by an additional one-to-one map between the M possible data values.
  • the decoding will first subject the M levels to an inverse map before applying the inverse of the above pseudo-random encodings.
  • the resulting pseudo-randomized data noise signals have a steady white noise spectrum and a
  • u N n can be encoded as R N n .
  • the use of stereo parity encoding allows the separate one BPSS data channels to be separately decoded while maintaining left/right symmetry in the audio when an odd number of one BPSS channels are used.
  • a data decoder can read from the basic one BPSS stereo parity data channel how to decode any other data channels (if any) present. In particular, this allows if desired moment-by moment variation of the data rate, either adaptively to the amount of data needing transmission or adaptively to the audio signal according to its " varying ability to mask the error signal caused by the hidden data channels.
  • the data rate allocated to say a video signal could be increased, allowing quite high quality video images in, say, heavy metal music-
  • One method conveys log 2 M bits for integer M in the less significant parts of audio words by conveying data in the M possible values of the remainder of the integer audio word after division by M, whereas the rounding quantization process used for the audio involves rounding to the nearest multiple of M. For M a power of 2, this reduces to conventional quantization to log ⁇ l fewer bits.
  • Each of the expansion coefficients w (k) can, if desired, be separately pseudo-randomized before the final length M word is formed. Again, this generalizes the binary case described above where the M j 's equaled 2.
  • a second method for fractional bit rates especially suitable for very low data rates of l/q BPSS for integer q is to code data only in one out of every q audio samples.
  • the encoding schemes are as before but with a data sampling rate divided by q, and decoding involves the decoder trying out and attempting to decode each of the q possible sub ⁇ sequences until it finds out (e.g. by confirming a parity check encoded into the data) which one carries data.
  • a third method for fractional bit rates also codes data in the LSBs of q successive samples, but codes the data into different logical combinations of all q bits. For example, a data rate of l/q BPSS can be obtained by encoding data as the parity (Boolean sum) of the q LSBs. It turns out that this option is often capable of significantly less audio noise degradation than the simpler scheme of the second method.
  • a part of the advantage is that if one needs to modify the parity, then one can choose to modify that sample out of the q successive samples causing the least error in an original high-resolution audio signal, rather than being. forced, to alter a. fixed sample...
  • the quantizer rounding process introduces nonlinear distortion, but this distortion may be replaced by a benign white noise error at the same typical noise level by using the process of subtractive dither shown in figure 4.
  • the process comprises adding a dither noise before the quantizer and subtracting the same dither noise afterwards.
  • the statistics of the dither noise are suitable, it can be shown (see [1] , [2] ) that this results in the elimination of all correlations between the error signal across the subtractively dithered quantizer and the input signal.
  • One such suitable dither statistics is what we term RPDF dither, i.e. dither each of whose samples is statistically independent of other samples and with a rectangular probability distribution function (PDF) with peak levels ⁇ .STEP.
  • An audio word of B bits each of which is a pseudo-random binary sequence is a 2 -level approximation to a signal with RPDF statistics, so that the data noise signals considered above may be used as dither signals for dithering audio to eliminate nonlinear quantization distortions and modulation noise.
  • the M-level data noise signals described above in section 2.3 using the remainder modulo M for data if made to be of a pseudo ⁇ random form by a pseudo-random data encoding/decoding process, can be used as an M-level approximation to RPDF noise.
  • the spectrum of the error signal may be modified to match any desired psychoacoustic criteria by the process of noise shaping, discussed for example in refs. [1], [4], [12], [17] - [19] .
  • Noise shaping may be static (i.e. adjusting the spectrum in a time-invariant way) and made to minimize audibility or optimize perceptual quality at low noise levels, or alternatively it can be made adaptive to the audio signal spectrum so as to be optimally masked by the instantaneous masking thresholds of audio signals at a higher level.
  • loud audio signals may well allow an increased error energy to be masked, thereby allowing a higher data rate to be transmitted in the hidden data channels during loud audio passages.
  • the error feedback filter H iz '1 must include a 1- sample delay factor z '1 in order to be implementable recursively, and the originally white spectrum of the subtractively dithered quantizer is filtered by the frequency response of the noise shaping filter
  • fig. 7 shows an alternative "outer" form of noise shaping architecture described in ref. [4] , that is equivalent to fig. 6 if one puts
  • This data noise signal has (discrete -M-level), RPDF statistics, and.may.be used as the dither noise source in figures 6 or 7, as shown in figs 8 and 9. where the quantizer is simply the process of rounding the signal word to the nearest integer multiple of M LSB's (or the nearest level if the levels are placed uniformly at other than the integer multiple of M LSB's) .
  • the noise shaping has no effect on the information representing the data in the output audio word, but merely modifies the process by which the quantization of the audio is performed so as to minimize the perceptual effect of the added data noise on the audio. It is remarkable that this output signal, being the output of a noise-shaped subtractively dithered quantizer, automatically incorporates all the benefits of noise shaped subtractive dither without the audio-only listener needing any special subtractive decoding apparatus.
  • the noise shaping can be varied in any way desired without affecting reception of the data (provided only that no overflow occurs in the noise shaping loop near peak audio levels - fitting a clipper in the signal path before the quantizer to prevent this may be desirable) .
  • the noise-shaping process does not affect the way the signal is used by either audio or data end-users of the signal, and so does not need any standardization, but may be used in any way desired by the encoding operative to achieve any desired kind of static or dynamic noise shaping characteristic.
  • fig. 10 shows yet another implementation having identical performance to that shown in figs. 8 or 9. It is also evident that in a similar way, the data noise signal can be added and subtracted outside the "outer" noise shaper of fig. 9 rather than inside the noise shaper as shown.
  • noise shaping is preferably used for systems of adding buried data according to the methods of subtractive dither by the buried data as described above with reference to figs. 8 to 10, it may also be applied to those systems in which the buried data is not subtracted before the quantiser but only added after the quantizer, for example as in figs. 8b and 9b, where the subtraction node of Figures 8a and 9a immediately before the quantizer is omitted, or where the signal fed to this node is conventional additive pseudo-random dither noise rather than the psuedo-randomised data signal. Omission of the subtracted data noise signal or its substitution by conventional dither noise at the node before the quantizer typically loses some of the quality advantages.
  • Explicit coefficients for the noiseshaper filter H iz '1 that may be used to reduce the audibility of buried data on compact disc and other audio media at sampling rates of 44.1 or 48 kHz, with or without audio pre-emphasis are described in reference 12.
  • Recovery of the buried data is also straightforward, simply being recovery of the data noise signal by rejecting highest bits of the received audio word, or in the case of M-level. data.
  • the. inverse process to the encoding of reading the remainder of the audio word after division by M, i.e. resolving the least significant digits of the audio word via modulo M arithmetic.
  • This is followed by the inverse pseudo-random decoding process to recover the data before pseudo randomization, and then the data is handled as data in the usual way.
  • This decoding process is shown schematically in figure 11.
  • the data is encoded as integer coefficients w (k) with more than one base M: as in Eq. (2-7) above, the data is recovered by K successive divisions by - i to M ⁇ , at each stage discarding the fractional part, the K coefficients w (k) being the integer remainders of the division by M k+1 .
  • This is the same process shown in figure 11, but with K stages of the modulo division.
  • Vector quantizers quantize a vector signal y comprising n scalar signals (Yi-t - • • t Yi i n geometrical regions covering the n- dimensional space of n real variables.
  • a uniform vector quantizer divides the n-variable space into a grid of identical vector quantization cells that are translates of the cell C to the points of the grid G, and quantizes or rounds any point in the cell y + C to the point y g .
  • c,- 1 ⁇ ⁇ yi STEP V i l,...,n ⁇ , i.e. separate scalar quantization of the n variables.
  • the rhombic quantizer cell can be described geometrically by thinking of the original hypercubic cells as being colored white if m- 1 +...+m,, is even and black if m- 1 +...+ ⁇ is odd, forming a kind of n-dimensional checkerboard pattern of alternately black and white hypercubes. Then attach to each white hypercube that "pyramid" portion of each adjacent black hypercube lying between the center of the black hypercube and the common "face" with the white hypercube. The resulting solid is the rhombic cell C.
  • the rhombic quantizer cell C is a diamond-shape, being a square whose sides are rotated 45° relative to the channel axes, as shown in fig.12.
  • the rhombic quantizer cell C is a rhombidodecahedron, a 12-faced solid whose faces are rhombuses.
  • the rhombic quantizer cell C is a regular polytope unique to 4 dimensions termed the regular 24-hedroid .
  • the rhombic quantizer has grid G consisting of the points
  • n-signal dither noise vector (n 1# .. , ⁇ 1 is said to have a uniform probability distribution function in a region C of n-dimensional space if its joint probability distribution function is constant within the region C and zero outside it. This is the n-dimensional generalization of rectangular PDF dither for vector signals, and we denote the associated n-vector dither signal by r c .
  • noise shaping can be applied around such subtractive dither in exactly the same way as before, as shown in figs. 6 and 7, or in equivalent noise shaping architectures, the only difference being that any filtering is now applied to n parallel signal channels. It is also possible, if desired, to use an n x n matrix error feedback filter H(z 'x ) or H' (z '1 ) to make the noise shaping dependent on the vector direction, for example to optimize directional masking of noise by signals [9] , [10] .
  • this algorithm may involve unnecessary complication, since it can be shown that with the subtractive dither arrangement of fig. 4 with a uniform vector quantizer with quantization cell C, that a uniform PDF vector dither signal r D may be used for any other uniform quantization cell D sharing the same grid G, and will still eliminate nonlinear distortion and modulation noise in the output.
  • the resulting error signal from the subtractive dither arrangement of fig. 4 is a noise signal with uniform PDF statistics on the quantizer cell C of the uniform vector quantizer used.
  • a uniform PDF vector dither noise signal r D (V 17 .. ,v n ) given by v-
  • LSB level is shown in figure 13.
  • the dither used has a triangular PDF with peak levels ⁇ 1 LSB (so-called TPDF dither) with independent statistics at each discrete time instant, so as to eliminate modulation noise in nonsubtractive playback [2] , and is added before the quantizer in the noise shaping loop, but not subtracted in the noise shaping loop. This ensures that the added noise in nonsubtractive playback is noise shaped.
  • Subtractive playback of the extra dither is done, also as shown in fig. 13 by reconstituting the triangular ⁇ 1 LSB PDF dither at the playback stage, passing it through a noise shaping filter 1 - H (z 'x ) , and subtracting the filtered noise from the output audio word.
  • Subtractive playback of course reduces the extra noise energy caused by the non-discrete dither by a factor 3, although this will only be highly advantageous when the data noise signal has fairly low energy, e.g. at a data rate of 1 BPSS.
  • the triangular dither signal may be generated, in encoding, as proposed in the "autodither" proposal of ref. [3] by means of a pseudo-random logic look-up table or a logic network having the effect of a pseudo-random look-up table, from the less or least significant parts of the output audio word in the last K previous samples, where typically K may be 24, and can be reconstructed from the same audio word at the input of the system by the same look-up table or logic in the decoding stage. This is shown in the system of fig. 13 in fig. 14.
  • FIG. 13 and 14 are shown for the particular noise shaping architecture of fig. 6, similar ways of adding the extra triangular dither can be used with any other equivalent noise shaping architecture such as the outer form of figure 7 and fig. 10, again by adding the triangular dither just before the quantizer and subtracting it, via a noise shaping filter 1 - H iz '1 ) , only at the output of the decoder. It is clear that the points at which dither signals are added can be shifted around in various ways without affecting the functionality of the system.
  • a disadvantage of the methods for adding ⁇ 1 LSB triangular PDF dither shown in figs. 13 and 14 is that in these schematics, the noise shaping filter 1 -H iz '1 ) used for the triangular PDF dither and for the quantizer is identical. Especially in systems of subtractive dither where the noise shaping of the subtracted dither in the decoder is desirably standardised (see ref. [3]), this would not allow use of noise shaping around the quantizer with a non- standardised characteristic, such as for example noise shaping adaptive to the signal waveform level and spectrum to take advantage of auditory masking by the signal.
  • An alternative shown in fig. 15 avoiding this disadvantage uses a first possibly fixed or standardised filter 1 -H 1 (z '1 ) for the ⁇ 1 LSB triangular PDF dither noise subtractive decoding, but now uses the same filter in the encoding, and instead adds this filtered ⁇ 1 LSB triangular PDF dither noise to a point before the noise shaping loop.
  • the noise shaping loop around the quantizer may then use a second possibly different error feedback filter 2 (z '1 ) 'in place of H fz '1 ) to achieve any desired predetermined quantizer noise shaping characteristic 1 -H 2 (z '1 ) l including ones adaptive to the signal waveform.
  • the "data noise signal" used for dithering is given, for example, by Eqs. (5-8) where r, is the data noise signal of the last h bits of the i'th-channel audio word (with the first channel being say left and the 2nd channel being say right) , and u being the parity of bits 15-h of the left and right audio words.
  • the data noise signal for the left channel is then L 0 - 2 h u and for the right channel is R Q , where L 0 and R Q are the respective integer words represented by the last h bits of the audio word formed by the data in the two channels.
  • Any alternative data noise signal may be used that represents an appropriate uniform PDF vector dither as described in section 5.3, such as for example that given by Algorithm (5-5) .
  • a first generalization is that the same process may be applied to other audio wordlengths besides the 16 bit wordlength of CD, for example to the 10 bit wordlengths of NICAM encoded digital signals or to the 20 bit or 24bit wordlengths used in some professional audio applications when it is desired to hide data in the audio words.
  • the inventors described a proposal to add data at the 24th bit in studio operations on signals to detect whether or not they had been modified, and the data encoding techniques of this invention can be used in that application to minimize the audibility of the modification of the signal proposed there.
  • the second generalization is that one can also apply stereo parity coding to the case where one replaces the 2 -level data in the last h bits by an M-level case for any integer M > 1.
  • data is coded into the residue of the audio words of the two channels after division by M, and the "stereo parity" data channel is coded into the Boolean sum of the binary LSB in the two channels of the integer parts of the audio words divided by M.
  • This case is handled identically to that in the previous sub-section 6.3 except that 2 is replaced throughout by M, and the phrase "last h bits" is replaced by "residue modulo M" .
  • a third generalization instead considers n channels rather than two.
  • This kind of efficient low bit-rate culling of data capacity could be used, for example, with successive samples within individual sub-band channels of a sub-band data compression system. Its application is not confined to audio; culling say 1 bit per 6 10-bit video samples in a digital video recorder with a video data rate of 200 Megabits per second would give a data rate typically enough for 4 16-bit audio channels or a consumer-grade additional data-reduced video signal while losing only 0.6 dB in video S/N in the original video channel.

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Abstract

Un procédé et un appareil servant à coder des données numériques dans des mots numériques représentant des formes d'onde de signaux, consiste à modifier les chiffres moins importants des mots numériques représentant des formes d'onde de signaux en fonction des données numériques. Ceci est effectué en rendant pseudo-aléatoires les données numériques, ce qui forme des mots de bruit de données ayant des niveaux qui sont petits par rapport à ceux des mots de forme d'onde, en soustrayant les mots de données rendus pseudo-aléatoires des mots de forme d'onde pour produire un mot de forme d'onde à vibrations, pour quantifier ensuite le mot de forme d'onde à vibrations et ajouter le mot de bruit de données au mot quantifié afin de produire une sortie de bruit réduit portant des informations représentant les données numériques dans leurs chiffres les moins importants.
PCT/GB1994/000297 1993-02-15 1994-02-15 Transmission de mots contenant des donnees numeriques representant une forme d'onde de signal Ceased WO1994018762A1 (fr)

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GB2293297B (en) * 1994-09-13 1999-01-20 Sony Uk Ltd Dithered data coding
WO2000026908A1 (fr) * 1998-10-29 2000-05-11 Koninklijke Philips Electronics N.V. Incorporation de donnees supplementaires dans un signal d'information
EP0866618A3 (fr) * 1997-03-20 2000-07-05 Motorola, Inc. Filtrage adaptif utilisé dans la compression de données et la reconstruction de signaux
EP1143438A1 (fr) * 1995-08-25 2001-10-10 Sony Corporation Supports d'enregistrement de signaux
EP1080545A4 (fr) * 1998-05-12 2001-11-14 Solana Technology Dev Corp Transport de donnees numeriques cachees
WO2002017318A1 (fr) * 2000-08-25 2002-02-28 Koninklijke Philips Electronics N.V. Procede et appareil permettant de reduire la longueur de mot d'un signal d'entree numerique et procede et appareil permettant de recuperer ledit signal d'entree numerique
US6792542B1 (en) 1998-05-12 2004-09-14 Verance Corporation Digital system for embedding a pseudo-randomly modulated auxiliary data sequence in digital samples
EP1365593A3 (fr) * 1996-07-15 2004-11-17 SNELL & WILCOX LIMITED Compression de signaux vidéo
EP1189449A3 (fr) * 1995-12-27 2007-05-02 Sony Corporation Codage hiérarchique de signaux vidéo
US7299189B1 (en) 1999-03-19 2007-11-20 Sony Corporation Additional information embedding method and it's device, and additional information decoding method and its decoding device
GB2524784A (en) * 2014-04-02 2015-10-07 Peter Graham Craven Transparent lossless audio watermarking

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DE3806411A1 (de) * 1988-02-29 1989-09-07 Thomson Brandt Gmbh Verfahren zur uebertragung eines tonsignals und eines zusatzsignals
WO1992022060A1 (fr) * 1991-05-29 1992-12-10 Pacific Microsonics, Inc. Systeme ameliore de codage/decodage de signaux

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US4857927A (en) * 1985-12-27 1989-08-15 Yamaha Corporation Dither circuit having dither level changing function
DE3806411A1 (de) * 1988-02-29 1989-09-07 Thomson Brandt Gmbh Verfahren zur uebertragung eines tonsignals und eines zusatzsignals
WO1992022060A1 (fr) * 1991-05-29 1992-12-10 Pacific Microsonics, Inc. Systeme ameliore de codage/decodage de signaux

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WO1995018523A1 (fr) * 1993-12-23 1995-07-06 Philips Electronics N.V. Procede et appareil de codage de sons numeriques codes en bits multiples par vibration adaptative soustractive, par insertion de bits de canaux enterres et par filtrage, et appareil de codage et de decodage de mise en oeuvre de ce procede
GB2293297B (en) * 1994-09-13 1999-01-20 Sony Uk Ltd Dithered data coding
US8301014B2 (en) 1995-08-25 2012-10-30 Sony Corporation Signal recording/reproducing method and apparatus, signal record medium and signal transmission/reception method and apparatus
US7428369B2 (en) 1995-08-25 2008-09-23 Sony Corporation Signal recording/reproducing method and apparatus, signal record medium and signal transmission/reception method and apparatus
EP1143438A1 (fr) * 1995-08-25 2001-10-10 Sony Corporation Supports d'enregistrement de signaux
US6345145B1 (en) 1995-08-25 2002-02-05 Sony Corporation Signal recording/reproducing method and apparatus, signal record medium and signal transmission/reception method and apparatus
US6345146B1 (en) 1995-08-25 2002-02-05 Sony Corporation Signal recording/reproducing method and apparatus, signal record medium and signal transmission/reception method and apparatus
EP1189449A3 (fr) * 1995-12-27 2007-05-02 Sony Corporation Codage hiérarchique de signaux vidéo
EP1365593A3 (fr) * 1996-07-15 2004-11-17 SNELL & WILCOX LIMITED Compression de signaux vidéo
EP2271103A3 (fr) * 1996-07-15 2013-01-16 Amstr. Investments 4 K.G., LLC Compression de signaux vidéo
EP0866618A3 (fr) * 1997-03-20 2000-07-05 Motorola, Inc. Filtrage adaptif utilisé dans la compression de données et la reconstruction de signaux
US6792542B1 (en) 1998-05-12 2004-09-14 Verance Corporation Digital system for embedding a pseudo-randomly modulated auxiliary data sequence in digital samples
EP1080545A4 (fr) * 1998-05-12 2001-11-14 Solana Technology Dev Corp Transport de donnees numeriques cachees
US7460667B2 (en) 1998-05-12 2008-12-02 Verance Corporation Digital hidden data transport (DHDT)
WO2000026908A1 (fr) * 1998-10-29 2000-05-11 Koninklijke Philips Electronics N.V. Incorporation de donnees supplementaires dans un signal d'information
US7299189B1 (en) 1999-03-19 2007-11-20 Sony Corporation Additional information embedding method and it's device, and additional information decoding method and its decoding device
WO2002017318A1 (fr) * 2000-08-25 2002-02-28 Koninklijke Philips Electronics N.V. Procede et appareil permettant de reduire la longueur de mot d'un signal d'entree numerique et procede et appareil permettant de recuperer ledit signal d'entree numerique
GB2524784A (en) * 2014-04-02 2015-10-07 Peter Graham Craven Transparent lossless audio watermarking
GB2524784B (en) * 2014-04-02 2018-01-03 Law Malcolm Transparent lossless audio watermarking
US9940940B2 (en) 2014-04-02 2018-04-10 Peter Graham Craven Transparent lossless audio watermarking

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