DTS Coherent Acoustics encoder

Project: DTS Coherent Acoustics encoder
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State	Stalled
Members	Danny Witberg
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Description	Make my own DTS encoder
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This project descibes a possible hardware implementation of a DTS Coherent Acoustics Core Audio encoder. The DTS Coherent Acoustics coding system is used as a file format for playing multichannel digital audio, but also for transporting multichannel audio over a digital audio connection. It is frequently used as the preferred CODEC in movies on DVD, Bluray or downloadable format. The coding system offers an exsensible high quality compressed multichannel audio stream. The core stream has a maximum of 7 channels of fullband audio, with 1 low frequency effect channel, and a resolution of 24 bits and a sample rate of 48kHz. Apart from this core audio stream, an extended stream can be offered with additional channels and/or higher sampling rates. A decoder for the datastream must be able to decode the core stream, but decoding the extended is optional. This way, backwards compatibility is provided. The extended stream can contain up to 32 fullband channels, frequency extension for core audio streams as well as extended audio streams, and resolution enhancements for all channels up to lossless quality.

This project describes the hardware implementation of a core audio stream encoder, using an FPGA and Digital Signal Processors. It accepts up to 4 stereo SP/DIF digital audio connections, or a single ADAT multichannel stream, and converts it to the DTS compressed audio link. If you plan to use this project for anything other than personal education, you should ask DTS Inc. if you have to obtain a licence: http://www.dts.com/professionals/licensing.aspx

How the DTS Coherent Acoustics CODEC works

A fullband channel is compressed in various ways, but always begins by dividing the channel into 32 subbands by means of a quadrature mirror filter. After obtaining these 32 subbands, every subband can, but does not have to be, compressed with use of a adaptive differential method, also named ADPCM. This algorithm is used to send the difference that the signal has, compared to the previous sample, instead of the actual amplitude. In slow changing signals, low frequencies, this can be a very effective method to reduce the amplitude of the signal that has to be encoded. After this first step, linear scalar quantization is used to compress the amount of data that has to be transmitted. In other words, a clevery chosen lookup table is used to descibe the amplitude of the signal. After this quantization, the data may be further compressed by use of a huffman code. Finally, the remaining data is placed in the core audio stream.

The Quadrature Mirror Filter (QMF)

The quadrature mirror filter or QMF filter is a set of filters, which complements each other to filter a frequency range into a number of subsets. After recomposition, the result reconstructs or closely reconstructs the original. The most effective way to do the required 32 band QMF is by using a FFT or Fast Fourier Transformation. The process begins by rearranging the samples in order to obtain the complementing nature of the filter. After this process, an IDCT transformation is implemented with an FFT routine. In modern DSP processors, this FFT routine is greatly optimized and can be executed quite fast. The process if visualized with the following example, for a QMF filter of 8 subbands:

Adaptive Differential Pulse Code Modulation

The subband output of the QMF filter can be encoded using an ADPCM scheme, and can help reducing the amount of data that has to be encoded. The principle is that instead of the actual amplitude of the signal is encoded, the difference is encoded instead. This can be a great help in reducing the stream data, if the input signal does not alter that much from sample to sample. In subband samples, this is likely to be the case. It is measured by encoding the input samples with the ADPCM scheme, and then comparing it to the original. If the so called prediction gain is high enough, the samples can then be converted using ADPCM.

Quantization

Quantization in digital signal processing, is a process of converting a number of input samples into a smaller number of output samples. A normal analog to digital converting processing is an everyday example of such a process. The analog signal, representing an infinite number of possible values, are converted into a given number of output signal, thus digitizing the input signal. In case of the mid tread linear scalar quantization used in DTS, the 24 bit input signal is converted in a 6 or 7 bit output signal. The way these converting tables work is logarithmic, because the perceptive hearing of the human ear is also logarithmic. Small differences in values can be encoded with a greater precision than larger ones. With a 6 bit table, there are 2.2 decibels per step, and half that in case of a 7 bit table.

PCB design

The following artwork of the PCB has been created to test the workings of the encoder: