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Figure shows the typical sequence
of operations performed in the compression of still images and video and audio
data streams. The following example describes the compression of one image:
1.The preparation step (here
picture preparation) generates an appropriate digital representation of the
information in the medium being compressed. For example, a picture might be
divided into blocks of 8 8 pixels with a fixed number of bits per pixel.
2.The processing step (here picture
processing) is the first step that makes use of the various compression
algorithms. For example, a transformation from the time domain to the frequency
domain can be performed using the Discrete Cosine Transform (DCT). In the case
of interframe coding, motion vectors can be determined here for each 88 pixel
block.
3.Quantization takes place after
the mathematically exact picture processing step. Values determined in the
previous step cannot and should not be processed with full exactness; instead
they are quantized according to a specific resolution and characteristic curve.
This can also be considered equivalent to the -law and A-law, which are
used for audio data [JN84]. In the transformed domain, the results can be
treated differently depending on their importance (e.g., quantized with different
numbers of bits).
4.Entropy coding starts with a
sequential data stream of individual bits and bytes. Different techniques can
be used here to perform a final, lossless compression. For example, frequently
occurring long sequences of zeroes can be compressed by specifying the number
of occurrences followed by the zero itself.
Picture processing and
quantization can be repeated iteratively, such as in the case of Adaptive
Differential Pulse Code Modulation (ADPCM). There can either be “feedback” (as
occurs during delta modulation), or multiple techniques can be applied to the data
one after the other (like interframe and intraframe coding in the case of
MPEG). After these four compression steps, the digital data are placed in a
data stream having a defined format, which may also integrate the image
starting point and type of compression. An error correction code can also be
added at this point.
Figure shows the compression process applied
to a still image; the same principles can also be applied to video and audio
data.
Decompression is the inverse
process of compression. Specific coders and decoders can be implemented very
differently. Symmetric coding is characterized by comparable costs for encoding
and decoding, which is especially desirable for dialogu applications. In an
asymmetric technique, the decoding process is considerably less costly
than the coding process. This is intended for applications where compression is
performed once and decompression takes place very frequently, or if the decompression
must take place very quickly. For example, an audio-visual course module is
produced once, but subsequently decoded by the many students who use it. The
main requirement is real-time decompression. An asymmetric technique can
be used to increase the quality of the compressed images.
The following section discusses
some basic compression techniques. Subsequent sections describe hybrid
techniques frequently used in the multimedia field
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