Page 194 - DCAP303_MULTIMEDIA_SYSTEMS

Multimedia Systems

notes The psychovisual redundancies exist should not come as a surprise, since
human perception of the information in an image normally does not involve
quantitative analysis of every pixel value in the image.
The world’s first commercial broadcast automation audio compression system
was developed by Oscar Bonello, an Engineering professor at the University
of Buenos Aires.

11.5 image Compression Models

A compression system consists of two distinct structural blocks: an encoder and a decoder. An
input image f(x, y) is fed into the encoder, which creates a set of symbols from the input data.
After transmission over the channel, the encoded representation is fed to the decoder, where a
reconstructed output image f^(x, y) is generated. In general, f^(x, y) may or may not been exact
replica of f(x, y). If it is, the system is error free or information preserving; if not, some level of
distortion is present in the reconstructed image. Both the encoder and decoder shown in Figure
11.2 consist of two relatively independent functions or sub-blocks. The encoder is made up of a
source encoder, which removes input redundancies, and a channel encoder, which increases the
noise immunity of the source encoder’s output. As would be expected, the decoder includes a
channel decoder followed by a source decoder. If the channel between the encoder and decoder
is noise free (not prone to error), the channel encoder and decoder are omitted, and the general
encoder and decoder become the source encoder and decoder, respectively.
figure 11.2: a General Compression system Model

11.5.1 the source encoder and Decoder
The source encoder is responsible for reducing or eliminating any coding, interpixel or psychovisual
redundancies in the input image. The specific application and associated fidelity requirements
dictate the best encoding approach to use in any given situation. Normally, the approach can be
modelled by a series of three independent operations. As Figure 11.3 (a) shows, each operation
is designed to reduce one of the three redundancies. Figure 11.3 (b) depicts the corresponding
source decoder. In the first stage of the source encoding process, the mapper transforms the input
data into a (usually nonvisual) format designed to reduce interpixel redundancies in the input
image. This operation generally is reversible and may or may not reduce directly the amount of
data required to represent the image.
figure 11.3: (a) source encoder and (b) source Decoder Model

f(x, y) Mapper Quantizer Symbol Channel
encoder

a
( ) Source encoder
Channel Symbol Inverse f(x, y)
decoder mapper

b
( ) Source decoder

188 LoveLy professionaL University