Image Transmission Systems for Wireless Channels
Theories, Alogorithms and Applications
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In the modern day, many novel information technologies involve the transmission of imagery over noisy channels such as satellite andwireless mobile channels. In general, a low-bit-rate image transmission system requires an outstanding image encoder that provides both an excellent quality for the reconstructed image anda high compression ratio. However, the resulting compressed bit stream becomes highly sensitive to channel noise. There have beenseveral approaches to add error resiliency to an image coder. For instance, the joint source-channel technique (JSC) techniques are developed by consid...
In the modern day, many novel information
technologies involve the transmission of imagery
over noisy channels such as satellite and
wireless mobile channels. In general, a low-bit-rate
image transmission system requires an outstanding
image encoder that provides both an excellent
quality for the reconstructed image and
a high compression ratio. However, the resulting
compressed bit stream becomes highly sensitive to
channel noise. There have been
several approaches to add error resiliency to an
image coder. For instance, the joint source-channel
technique (JSC) techniques are developed by
considering both source and channel codecs. This book
is focused on a kind of this technique known as
source-controlled channel decoding. In particular,
the residual redundancy in MPEG-4 compressed imagery
is considered. Here an embedded zerotree wavelet
(EZW) algorithm is used to generate a compressed bit
stream, which is then passed through a
ring convolutional encoder (CE) and a CPFSK
modulation system. Moreover, the design of trellis
codes using ring convolutional
codes and CPFSK for MAP decoding is also described.
technologies involve the transmission of imagery
over noisy channels such as satellite and
wireless mobile channels. In general, a low-bit-rate
image transmission system requires an outstanding
image encoder that provides both an excellent
quality for the reconstructed image and
a high compression ratio. However, the resulting
compressed bit stream becomes highly sensitive to
channel noise. There have been
several approaches to add error resiliency to an
image coder. For instance, the joint source-channel
technique (JSC) techniques are developed by
considering both source and channel codecs. This book
is focused on a kind of this technique known as
source-controlled channel decoding. In particular,
the residual redundancy in MPEG-4 compressed imagery
is considered. Here an embedded zerotree wavelet
(EZW) algorithm is used to generate a compressed bit
stream, which is then passed through a
ring convolutional encoder (CE) and a CPFSK
modulation system. Moreover, the design of trellis
codes using ring convolutional
codes and CPFSK for MAP decoding is also described.
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