Audio & Multimedia MPEG Audio Layer-3

• History
• Quality
• Details

 Fraunhofer IDMT

History

In 1987, the Fraunhofer IIS started to work on perceptual audio coding in the framework of the EUREKA project EU147, Digital Audio Broadcasting (DAB). In a joint cooperation with the University of Erlangen (Prof. Dieter Seitzer), the Fraunhofer IIS finally devised a very powerful algorithm that is standardized as ISO-MPEG Audio Layer-3 (IS 11172-3 and IS 13818-3).

Without data reduction, digital audio signals typically consist of 16 bit samples recorded at a sampling rate more than twice the actual audio bandwidth (e.g. 44.1 kHz for Compact Discs). So you end up with more than 1.400 Mbit to represent just one second of stereo music in CD quality. By using MPEG audio coding, you may shrink down the original sound data from a CD by a factor of 12, without losing sound quality. Factors of 24 and even more still maintain a sound quality that is significantly better than what you get by just reducing the sampling rate and the resolution of your samples. Basically, this is realized by perceptual coding techniques addressing the perception of sound waves by the human ear.

Using MPEG audio, one may achieve a typical data reduction of

still maintaining the original CD sound quality.

By exploiting stereo effects and by limiting the audio bandwidth, the coding schemes may achieve an acceptable sound quality at even lower bitrates. MPEG Layer-3 is the most powerful member of the MPEG audio coding family. For a given sound quality level, it requires the lowest bitrate - or for a given bitrate, it achieves the highest sound quality.

Sound Quality

Some typical performance data of MPEG Layer-3 are:

In all international listening tests, MPEG Layer-3 impressively proved its superior performance, maintaining the original sound quality at a data reduction of 1:12 (around 64 kbit/s per audio channel). If applications may tolerate a limited bandwidth of around 10 kHz, a reasonable sound quality for stereo signals can be achieved even at a reduction of 1:24.

For the use of low bit-rate audio coding schemes in broadcast applications at bitrates of 60 kbit/s per audio channel, the ITU-R recommends MPEG Layer-3. (ITU-R doc. BS.1115)

Details

Filter bank

The filter bank used in MPEG Layer-3 is a hybrid filter bank which consists of a polyphase filter bank and a Modified Discrete Cosine Transform (MDCT). This hybrid form was chosen for reasons of compatibility to its predecessors, Layer-1 and Layer-2.

Perceptual Model

The perceptual model mainly determines the quality of a given encoder implementation. It uses either a separate filter bank or combines the calculation of energy values (for the masking calculations) and the main filter bank. The output of the perceptual model consists of values for the masking threshold or the allowed noise for each coder partition. If the quantization noise can be kept below the masking threshold, then the compression results should be indistinguishable from the original signal.

Joint Stereo

Joint stereo coding takes advantage of the fact that both channels of a stereo channel pair contain far the same information. These stereophonic irrelevancies and redundancies are exploited to reduce the total bitrate. Joint stereo is used in cases where only low bitrates are available but stereo signals are desired.

Quantization and Coding

A system of two nested iteration loops is the common solution for quantization and coding in a Layer-3 encoder.

Quantization is done via a power-law quantizer. In this way, larger values are automatically coded with less accuracy and some noise shaping is already built into the quantization process.

The quantized values are coded by Huffman coding. As a specific method for entropy coding, Huffman coding is lossless. This is called noiseless coding because no noise is added to the audio signal.

The process to find the optimum gain and scalefactors for a given block, bit-rate and output from the perceptual model is usually done by two nested iteration loops in an analysis-by-synthesis way:

• Inner iteration loop (rate loop)
   
  The Huffman code tables assign shorter code words to (more frequent) smaller quantized values. If the number of bits resulting from the coding operation exceeds the number of bits available to code a given block of data, this can be corrected by adjusting the global gain to result in a larger quantization step size, leading to smaller quantized values. This operation is repeated with different quantization step sizes until the resulting bit demand for Huffman coding is small enough. The loop is called rate loop because it modifies the overall coder rate until it is small enough.


• Outer iteration loop (noise control/distortion loop)
   
  To shape the quantization noise according to the masking threshold, scalefactors are applied to each scalefactor band. The systems starts with a default factor of 1.0 for each band. If the quantization noise in a given band is found to exceed the masking threshold (allowed noise) as supplied by the perceptual model, the scalefactor for this band is adjusted to reduce the quantization noise. Since achieving a smaller quantization noise requires a larger number of quantization steps and thus a higher bitrate, the rate adjustment loop has to be repeated every time new scalefactors are used. In other words, the rate loop is nested within the noise control loop. The outer (noise control) loop is executed until the actual noise (computed from the difference of the original spectral values minus the quantized spectral values) is below the masking threshold for every scalefactor band (i.e. critical band).