Space-Time Super-Resolution from a Single Video

Oded Shahar, Alon Faktor, Michal Irani

Research output: Contribution to journalConference articlepeer-review


Spatial Super Resolution (SR) aims to recover fine image details, smaller than a pixel size. Temporal SR aims to recover rapid dynamic events that occur faster than the video frame-rate, and are therefore invisible or seen incorrectly in the video sequence. Previous methods for Space-Time SR combined information from multiple video recordings of the same dynamic scene. In this paper we show how this can be done from a single video recording. Our approach is based on the observation that small space-time patches ('ST-patches', e.g., 5x5x3) of a single 'natural video', recur many times inside the same video sequence at multiple spatio-temporal scales. We statistically explore the degree of these ST-patch recurrences inside 'natural videos', and show that this is a very strong statistical phenomenon. Space-time SR is obtained by combining information from multiple ST-patches at sub-frame accuracy. We show how finding similar ST-patches can be done both efficiently (with a randomized-based search in space-time), and at sub-frame accuracy (despite severe motion aliasing). Our approach is particularly useful for temporal SR, resolving both severe motion aliasing and severe motion blur in complex 'natural videos'.
Original languageEnglish
Pages (from-to)60
Number of pages8
Journal2011 Ieee Conference On Computer Vision And Pattern Recognition (Cvpr)
StatePublished - 2011
EventIEEE Conference on Computer Vision and Pattern Recognition (CVPR) - Colorado Springs, CO
Duration: 20 Jun 201125 Jun 2011


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