| Summary: | 博士 === 國立交通大學 === 電子工程系 === 88 === In Shannon''s theory, source coding and channel coding can be
treated separately without sacrificing the overall optimality.
In a practical system, it may not be to identify the source and the channel models perfectly;
thus, the theory may not be valid if either of the following
two situations occur: (a) the source coder is sub-optimal, or (b) the channel
coder cannot achieve the error-free condition. In this thesis, we study the
noise effects on the combined source and channel coding and present a few combined
coding algorithms for noisy channels.
This thesis is divided into three parts.
The first part describes a global motion parameter estimation method.
This method can be used to segment an image sequence
into objects of different motion.
For any two image pixels belonging to the same moving object,
constrained by the image projection geometry,
their global motion components are bounded by a fixed relationship.
Therefore, by examining the measured motion vectors
we are able to group pixels into objects
and, at the same time, identify the global motion parameters.
Furthermore, because the block shape is distorted due to camera zooming, a
deformable block motion estimation scheme is suggested to recover the object
local motion vectors.\ \indent
In the second part, given the weight distribution of
a linear block code and the weight of the Hamming distance between a transmitted
codeword $v_t$ and a decoded codeword $v_d$, we derive the error
probability that the transmitted codeword $v_t$ is decoded to $v_d$.
Our new method can estimate the upper bound of the bit
error probability in the case of the linear block code used for the binary
symmetric channel. Most existing quantizer designs do not take into
account the channel
characteristics. Based on the estimated upper bound, we propose a combined quantizer and linear
error control code design for noisy channels.\ \indent
In the third part, we present a quantizer that achieves the best
overall performance when its outputs are transmitted over
a fading channel.
First, a probalistic model describing a fading channel with binary
PSK or FSK modulation is derived. Then, we
propose a procedure of designing the
optimal quantizer for the slow fading channel by extending a previous work on
the combined source/channel quantizer design.
Next, we look into the structure
of our quantizer to find the theoretical grounds behind its superior performance. We also compare
this combined source/channel coder against the conventional separated
source/channel coder and identify the preferred operating regions of these two
systems. A transform image coding system over a fading channel is
designed based on the preceding principles. Simulations indicate that our quantizer
outperforms the channel-error-specific optimal quantizer, particularly when the channel
error probability is not precisely known.
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