Single image super resolution via sparse reconstruction

Maarten C. Kruithof; Adam W. M. van Eekeren; Judith Dijk; Klamer Schutte

doi:10.1117/12.919036

8 June 2012 Single image super resolution via sparse reconstruction

Maarten C. Kruithof, Adam W. M. van Eekeren, Judith Dijk, Klamer Schutte

Proceedings Volume 8365, Compressive Sensing; 83650F (2012) https://doi.org/10.1117/12.919036
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms. Limitation of these methods are that the reconstruction only works if multiple frames are available furthermore these algorithms decreases the temporal resolution. In this paper we use a sparse representation of an overcomplete dictionary to significantly increase the resolution of a single low resolution image. This allows for a higher resolution gain and no loss in temporal resolution. We demonstrate this technique to improve the resolution of number plates images obtained from a near infrared roadside camera.

Citation Download Citation

Maarten C. Kruithof, Adam W. M. van Eekeren, Judith Dijk, and Klamer Schutte "Single image super resolution via sparse reconstruction", Proc. SPIE 8365, Compressive Sensing, 83650F (8 June 2012); https://doi.org/10.1117/12.919036

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