Simultaneous multi-frame MAP super-resolution video enhancement using spatio-temporal priors

Author

Borman, Sean ; Stevenson, Robert L.

Author_Institution

Dept. of Electr. Eng., Notre Dame Univ., IN, USA

Volume

3

fYear

1999

fDate

1999

Firstpage

469

Abstract

A simultaneous multi-frame super-resolution video reconstruction procedure, utilizing spatio-temporal smoothness constraints and motion estimator confidence parameters is proposed. The ill-posed inverse problem of reconstructing super-resolved imagery from the low resolution, degraded observations is formulated as a statistical inference problem and a Bayesian, maximum a-posteriori (MAP) approach is utilized for its approximate solution. The inclusion of motion estimator confidence parameters and temporal constraints result in higher quality super-resolution reconstructions with improved robustness to motion estimation errors

Keywords

Bayes methods; image enhancement; image reconstruction; inference mechanisms; motion estimation; Bayesian method; ill-posed inverse problem; maximum a-posteriori approach; motion estimation errors; motion estimator confidence parameters; simultaneous multi-frame MAP super-resolution; spatio-temporal priors; spatio-temporal smoothness constraints; statistical inference problem; temporal constraints; video enhancement; video reconstruction; Additive noise; Bayesian methods; Image reconstruction; Image resolution; Maximum a posteriori estimation; Motion estimation; Parameter estimation; Spatial resolution; Strontium; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on

Conference_Location

Kobe

Print_ISBN

0-7803-5467-2

Type

conf

DOI

10.1109/ICIP.1999.817158

Filename

817158