The problem how to convey maximum distinguishable video information while consuming minimum resources has long been investigated since Shannon's source channel separation theorem. The theorem is derived under the condition that all transmission errors can be corrected by the channel coding to an arbitrarily low probability. However, such a condition usually does not hold in a practical mobile video communication system given the limited resources, such as time, bandwidth, power and space. Therefore, the problem in a ...
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The problem how to convey maximum distinguishable video information while consuming minimum resources has long been investigated since Shannon's source channel separation theorem. The theorem is derived under the condition that all transmission errors can be corrected by the channel coding to an arbitrarily low probability. However, such a condition usually does not hold in a practical mobile video communication system given the limited resources, such as time, bandwidth, power and space. Therefore, the problem in a practical system can be formulated by "Given the source, channel, resources and system structure, how to optimally control the system parameters to minimize the end-to-end distortion." This book first derives analytical models and designs estimation algorithms to accurately predict the distortion given random source and random channel. Solutions with low complexity are then provided to minimize the end-to-end distortion in different applications from codec level to cross-layer level given the resource constraints in the practical system. The target audience of this book includes PhD and graduate students, researchers in the field, codec and system design engineers.
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