Computational Cost Reduction of Improved Super-Resolution Method Using Overlapped Block Matching

〈Summary〉 The improved super-resolution method that achieves dense motion estimation (DME) using overlapped block matching (OBM) remarkably improves the quality of reconstructed images for a given video sequence. However, this method has a drawback to increase the computational cost almost linearly to the number of overlapped blocks because DME using OBM allocates multiple motion vectors to a local region in the image restoration process. To solve this problem, in this paper we propose a method to reduce computational cost of the improved super-resolution method by considering the statistics of motion vectors obtained by DME using OBM. This method can reduce the entire computational cost up to 29.9 ∼ 49.1% depending on a given video sequence while completely maintaining the original performance of the improved super-resolution method using OBM. Also, we try to further reduce computational cost by relaxing the complete original performance preservation requirement. With this additional attempt, we can further reduce computational cost up to 16.9 ∼ 20.8% without serious deterioration of the quality of reconstructed images.