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A Framework for Fine-Granular Computational-Complexity Scalable Motion Estimation

Overview This paper presents a novel Motion Estimation (ME) framework that offers fine-granular computational-complexity scalability. In the proposed framework, the ME process is first partitioned into multiple search passes. A priority function is used to represent the distortion reduction efficiency of each pass. According to the predicted priority of each MacroBlock (MB), computational resources are then allocated effectively in a progressive way to achieve fine-granular computational-complexity scalability. Experiments show that the proposed scheme achieves progressively improved performance over a wide range of computational capabilities.

Further White Paper Details
Publisher	Institute of Electrical and Electronics Engineers	File Format	PDF
Date Published	March 2005
Format	White Papers
Topics	Scalability, Software Engineering

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