The Weizmann Institute of Science Faculty of Mathematics and Computer Science Vision and Robotics Seminar Matan Protter Technion will speak on Super-Resolution without explicit motion estimation Abstract: Super-resolution is the task of improving the optical resolution of a given low-quality image sequence. The motion in the sequence introduces different aliasing artifacts in each frame, which are then used by super-resolution algorithms to recover sub-pixel details. Since the motion is important for recovering sub-pixel details, it has been long assumed that motion estimation is a necessary step for any super-resolution algorithm. Indeed, when the motion is known, amazing results can be achieved. However, due to the complexity of motion estimation and the high accuracy required of it, successful super-resolution has been limited to processing sequences containing only global motion (such as translations) or very simple motion patterns. In this work, we challenge the assumption that explicit motion estimation is indeed required. Instead, we propose a method that avoids explicit motion estimation, relying on what could be interpreted as fuzzy motion estimation, in the sense that for each pixel several trajectories are considered and merged probabilistically. We put the fuzzy motion concept into use in two ways. This final algorithm we develop is surprisingly simple, and is very reminiscent of (but critically different from) the Non-Local-Means image sequence denoising algorithm. We display several results on sequences with general and complicated motion patterns, proving the ability of the proposed method to process such movies and provide true super-resolution outcome. Joint work with Michael Elad (Technion), Peyman Milanfar (UCSC) and Hiro Takeda (UCSC) The lecture will take place in the Lecture Hall, Room 1, Ziskind Building on Thursday, April 3, 2008 12:00 - 13:00