Selective Bayesian estimation for efficient super-resolution

Zoran A. Ivanovski, Lina Karam, Glen P. Abousleman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, a new approach to efficient and robust super-resolution is presented. Our method is based on selectively applying a Bayesian MAP estimator to image regions with high spatial activity. The degree of spatial activity is measured using the gradient of the estimated high-resolution image at each iteration. In addition, selective filtering is applied to enhance the visual quality of the estimated high-resolution image. The results obtained via simulation and with real video sequences demonstrate up to a 50% reduction in computational complexity, with improved visual quality, and higher SNR gains for magnification factors of four or more.

Original languageEnglish (US)
Title of host publicationProceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology
Pages433-436
Number of pages4
StatePublished - Dec 1 2004
EventFourth IEEE International Symposium on Signal processing and Information Technology, ISSPIT 2004 - Rome, Italy
Duration: Dec 18 2004Dec 21 2004

Publication series

NameProceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004

Other

OtherFourth IEEE International Symposium on Signal processing and Information Technology, ISSPIT 2004
CountryItaly
CityRome
Period12/18/0412/21/04

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Ivanovski, Z. A., Karam, L., & Abousleman, G. P. (2004). Selective Bayesian estimation for efficient super-resolution. In Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology (pp. 433-436). (Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004).