The  Weizmann  Institute  of  Science
                  Faculty of Mathematics and Computer Science
                          Vision and Robotics Seminar
                     Lecture Hall, Room 1, Ziskind Building
                         on Thursday, January 27, 2011

                                 Gilad Freedman
                         Hebrew University of Jerusalem
                                 will speak on
               Image and Video Upscaling from Local Self-Examples
We propose a new high-quality and efficient single-image upscaling technique
that extends existing example-based super-resolution frameworks. In our
approach we do not rely on an external example database or use the whole input
image as a source for example patches. Instead, we follow a local
self-similarity assumption on natural images and extract patches from extremely
localized regions in the input image. This allows us to reduce considerably the
nearest-patch search time without compromising quality in most images. Tests,
that we perform and report, show that the local-self similarity assumption
holds better for small scaling factors where there are more example patches of
greater relevance. We implement these small scalings using dedicated novel
non-dyadic filter banks, that we derive based on principles that model the
upscaling process. Moreover, the new filters are nearly-biorthogonal and hence
produce high-resolution images that are highly consistent with the input image
without solving implicit back-projection equations. The local and explicit
nature of our algorithm makes it simple, efficient and allows a trivial
parallel implementation on a GPU. We demonstrate the new method ability to
produce high-quality resolution enhancement, its application to video sequences
with no algorithmic modification, and its efficiency to perform real-time
enhancement of lowresolution video standard into recent high-definition
Technion Math Net-2 (TECHMATH2)
Editor: Michael Cwikel   <> 
Announcement from: Diana Mandelik   <>