Paper Info
Title
Super-resolution from a low- and partial high-resolution image pair
Abstract
The classical super-resolution (SR) setting starts with a set of low-resolution (LR) images related by subpixel shifts and tries to reconstruct a single high-resolution (HR) image. In some cases, partial observations about the HR image are also available. Trying to complete the missing HR data without any reference to LR ones is an inpainting (or completion) problem. In this paper, we consider the problem of recovering a single HR image from a pair consisting of a complete LR and incomplete HR image pair. This setting arises in particular when one wants to fuse image data captured at two different resolutions. We propose an efficient algorithm that allows to take advantage of both image data by first learning nonlocal interactions from an interpolated version of the LR image using patches. Those interactions are then used by a convex energy function whose minimization yields a super-resolved complete image.
Year
DOI
Venue
2014
10.1109/ICIP.2014.7025430
Image Processing
Keywords
Field
DocType
image fusion,image resolution,high-resolution image,high-resolution image pair,image data fusion,low-resolution images,super-resolution,Douglas-Rachford algorithm,graph-regularization,inpainting,nonlocal patch-based methods,super-resolution,total variation
Computer vision,Feature detection (computer vision),Pattern recognition,Image texture,Computer science,Interpolation,Sub-pixel resolution,Regular polygon,Inpainting,Minification,Artificial intelligence,Subpixel rendering
Conference
Citations 
PageRank 
References 
2
0.36
17
Authors
4
Name
Order
Citations
PageRank
Moncef Hidane120.36
Jean-François Aujol221.04
Y. Berthoumieu338951.66
Charles-Alban Deledalle438724.00