In the multiframe image super-resolution (SR) methods a sequence of low-resolution (LR) images is used to create a high-resolution (HR) image. In all aforegoing methods, all of the LR images were registered with respect to one of existing images (called reference image) and their samples were mapped on an up-scaled grid of this reference image (called reference grid (RG)). However, the use of this RG may cause the samples appears with a highly non-uniform distribution. Additionally, final precision and quality may be dependent on the selection of reference image. In this paper a new RG which reduces the non-uniformity of sample distribution is proposed. This RG is produced by incorporating all of the images; therefore the final result is not dependent on the selection of reference image. We also propose a method to find this RG (will be referred as centroid RG). Moreover, this RG is unique.

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