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Depth map optimization based on adaptive chrominance image segmentation

The development of Free Viewpoint Video (FVV) technique is the most promising multimedia processing fields in recent years. Depth map prediction is the key method in FVV. There are many methods to estimate depth map. Among them, combined temporal and interview prediction method is the most practical which can save much data processing bandwidth, without additional hardware resources and computation time consumption. But block estimation based depth map has much block effect and prediction noises, especially at the object boundary and large continuous areas. This paper presents an adaptive chrominance image segmentation method to process the depth map prediction noises getting by combined temporal and interview prediction method. Experiment results show that this method can enhance the depth map quality efficiently with less calculation complexity, and is practical for hardware circuit realization and high performance real time processing.