Super-resolution in practice: the complete pipeline from image capture to super-resolved subimage creation using a novel frame selection method

Maria Petrou, Mohamed H. Jaward, Shengyong Chen, Mark Briers

Research output: Contribution to journalArticleResearchpeer-review

6 Citations (Scopus)


We present a complete super-resolution system using a camera, that is assumed to be on a vibrating platform and continually capturing frames of a static scene, that have to be super-resolved in particular regions of interest. In a practical system the shutter of the camera is not synchronised with the vibrations it is subjected to. So, we propose a novel method for frame selection according to their degree of blurring and we combine a tracker with the sequence of selected frames to identify the subimages containing the region of interest. The extracted subimages are subsequently co-registered using a state of the art sub-pixel registration algorithm. Further selection of the co-registered subimages takes place, according to the confidence in the registration result. Finally, the subimage of interest is super-resolved using a state of the art super-resolution algorithm. The proposed frame selection method is of generic applicability and it is validated with the help of manual frame quality assessment.

Original languageEnglish
Pages (from-to)441-459
Number of pages19
JournalMachine Vision and Applications
Issue number3
Publication statusPublished - May 2012
Externally publishedYes


  • Frame selection
  • Image quality assessment
  • Super-resolution

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