Fast and robust multiframe super resolution.

Journal Article (Journal Article)

Super-resolution reconstruction produces one or a set of high-resolution images from a set of low-resolution images. In the last two decades, a variety of super-resolution methods have been proposed. These methods are usually very sensitive to their assumed model of data and noise, which limits their utility. This paper reviews some of these methods and addresses their short-comings. We propose an alternate approach using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. This computationally inexpensive method is robust to errors in motion and blur estimation and results in images with sharp edges. Simulation results confirm the effectiveness of our method and demonstrate its superiority to other super-resolution methods.

Full Text

Duke Authors

Cited Authors

  • Farsiu, S; Robinson, MD; Elad, M; Milanfar, P

Published Date

  • October 2004

Published In

Volume / Issue

  • 13 / 10

Start / End Page

  • 1327 - 1344

PubMed ID

  • 15462143

Electronic International Standard Serial Number (EISSN)

  • 1941-0042

International Standard Serial Number (ISSN)

  • 1057-7149

Digital Object Identifier (DOI)

  • 10.1109/tip.2004.834669


  • eng