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This thesis investigates game theory based rate control algorithms for optimizing the bit allocation in video compression . The first algorithm utilizes the cooperative bargaining game in a MB level rate control algorithm to optimize the perceptual quality while guaranteeing "fairness" in bit allocation among macroblocks . The algorithm first allocates the target bits to frames based on their coding complexity ; a method to estimate the coding complexity of the remaining frames is proposed . Next , macroblocks of a frame play cooperative games such that each macroblock competes for a share of resources (bits ) to optimize its quantization scale while considering the human visual system (HVS ) perceptual property . Since the whole frame is an entity perceived by viewers , macroblocks compete cooperatively under a global objective of achieving the best quality with the given bit constraint . The major advantage of the proposed approach is that the cooperative game leads to an optimal and fair bit allocation strategy based on the Nash Bargaining Solution . Another advantage is that it allows multi -objective optimization with multiple decision makers (e .g . , macroblocks ) . The algorithm achieves accurate bit rate with good perceptual quality , and to maintain a stable buffer level . The second algorithm based on a non -cooperative strategic game is aimed for video object level bit allocation . We formulate a two -player bi -matrix game , in which the utilities of the players are pre -determined by a set of available strategies (i .e . , the possible quantization parameters ) . The game is non -deterministic in which the players' strategies are bound to a probability distribution over the set of available actions . The outcome of the game is a mixed strategy Nash equilibrium . The proposed algorithm achieves accurate bit rate regulation and smooth buffer occupancy . |
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