Adaptive frame selection for multi-frame super resolution

Abstract

Image super-resolution (SR) is a process to reconstruct a high-resolution (HR) image by fusing multiple low-resolution (LR) images. A critical step in image SR is accurate registration of the LR images, however the larger inter-frame motion can significantly affect the sub-pixel image registration, then it can also affect the output of HR reconstruction. So a novel Adaptive Frame Selection method is proposed in this paper for the reconstruction of multi-frame SR. It devises a framework to resolve the image SR reconstruction problem into two steps. Firstly, using the Optical flow algorithm to calculate the inter-frame motion estimation, designing an adaptive frame selection method to discard some of the larger inter-frame motion frames, then the less inter-frame motion of successive frames is obtained. Secondly, using the maximum a posteriori (MAP) based SR algorithm for the SR reconstruction. The experimental results indicate that the proposed algorithm has considerable effectiveness in terms of both objective measurements and visual evaluation. © 2012 Springer-Verlag GmbH.