Neighborhood issue in single-frame image super-resolution

Super-Resolution is the problem of generating one or a set of high-resolution images from one or a sequence of lowresolution frames. Most methods have been proposed for super-resolution based on multiple low resolution images of the same scene, which is called multiple-frame superresolution. Only a few approaches produce a highresolution image from a single low-resolution image, with the help of one or a set of training images from scenes of the same or different types. It is referred to as single-frame super-resolution. This article reviews a variety of singleframe Super-Resolution methods proposed in the recent years. In the paper, a new manifold learning method: locally linear embedding (LLE) and its relation with single-frame super-resolution is introduced. Detailed study of a critical issue: “Neighborhood Issue” is presented with related experimental results and analysis. And possible future research is given.

• Type: Conference
• Year: 2005
• Where: ICMCS
• Authors: K. Su, Qi Tian, Qing Xue, Nicu Sebe, Jingsheng Ma
• Keywords: ICMCS 2005, Low Resolution Images, Single Low-resolution Image, Single-frame Super-resolution