Image super-resolution by vectorizing edges
Journal
Lecture Notes in Computer Science
Journal Volume
6523 LNCS
Journal Issue
PART 1
Pages
435-445
Date Issued
2011
Author(s)
Hutchison, David
Abstract
As the resolution of output device increases, the demand of high resolution contents has become more eagerly. Therefore, the image super-resolution algorithms become more important. In digital image, the edges in the image are related to human perception heavily. Because of this, most recent research topics tend to enhance the image edges to achieve better visual quality. In this paper, we propose an edge-preserving image super-resolution algorithm by vectorizing the image edges. We first parameterize the image edges to fit the edges' shapes, and then use these data as the constraint for image super-resolution. However, the color nearby the image edges is usually a combination of two different regions. The matting technique is utilized to solve this problem. Finally, we do the image super-resolution based on the edge shape, position, and nearby color information to compute a digital image with sharp edges. © 2011 Springer-Verlag Berlin Heidelberg.
Subjects
Bézier curve; edge detection; interpolation; matting; mean-value coordinate; super-resolution; vectorization
Other Subjects
Color information; Digital image; Edge preserving; Edge shape; High resolution; Human perception; Image edge; Image super-resolution; matting; Mean values; Output devices; Research topics; Sharp edges; Super resolution; Vectorization; Visual qualities; Color information; Image super resolutions; Matting; Mean value coordinates; Recent researches; Super resolution; Vectorization; Visual qualities; Algorithms; Interpolation; Optical resolving power; Image enhancement; Interpolation; Optical resolving power; Edge detection; Edge detection
Type
conference paper