wilamowski-b-m-irwin-j-d-industrial-communication-systems-2011

Industrial Multimedia 27-5
FIGURE 27.4
Spatial redundancy examples.
application where loss of information is tolerated, lossy compressors are used, which allow a significant
increase in the compression rate. Concerning the complexity of the process, through an asymmetric
approach, it is possible to use quite complex algorithms in the source to optimize the quality and bit
rate (this can involve full two passes), while the decompression is performed in real time. However,
this approach cannot be used in live real-time applications, which are the more common, so usually
symmetric approaches are used, which have a similar complexity in compression and uncompression.
Finally, there are compressors that only use the spatial redundancy of images, that is, of the self-contained
information in an image, and compressors that also use the temporal redundancy, that is, the redundancy
created by similarities between consecutive frames.
Spatial redundancy exploits the proven statistical correlation between the pixels of an image, so it
allows us to extract a pixel’s value from the neighboring pixels. With this technique, it is not necessary
to reproduce each pixel of an image independently. In Figure 27.4, we can see two scenes of industrial
monitoring [SSA04]. On the left, there are wide areas in the image that have a similar value, which is
used by compressors to reduce the necessary bits to reproduce the information. On the left, all pixels in
the interval [28–32] have been represented in white, which gives an idea of the spatial redundancy and
its potential to reduce the number of bits to represent the multimedia information.
The temporal redundancy comes from the fact that a correlation between pixels of consecutive images
in a sequence exists. Between consecutive frames, less than 10% of pixels change their value in about
1% of the peak signal. In this way, images pixels can be predicted from the pixels of an image nearby in
the sequence. On the other hand, the fact that changes between consecutive images are caused by the
movement of some objects in the scene has caused the development of motion compensation coding
techniques. Figure 27.5 shows this in an industrial monitoring sequence captured at 25 frames/s. As we
can see, the difference between consecutive images is very little in this case, and for this reason, in this
type of sequence, the use of temporal redundancy allows us to obtain high rates of compression.
© 2011 by Taylor and Francis Group, LLC