A parametric technique for superresolution image reconstruction

Author

Bresler, Yoram ; Litke, Scott P.

Author_Institution

Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA

fYear

1990

fDate

3-6 Apr 1990

Firstpage

1205

Abstract

A model-based approach for superresolution signal reconstruction from noisy bandlimited Fourier data is proposed. The approach combines the virtues of parametric and nonparametric techniques by maximum-likelihood fitting of the data by a mixture of exponentials and smooth basis functions. Performance bounds are derived and analyzed, and a model computationally efficient algorithm is described. The performance of the algorithm in simulations closely matches the bounds over a wide range of operating conditions. Overall, the reconstructions are far superior to those obtained by traditional Fourier transform processing

Keywords

Fourier transforms; computerised picture processing; parameter estimation; exponentials; maximum-likelihood fitting; noisy bandlimited Fourier data; parametric technique; smooth basis functions; superresolution image reconstruction; Algorithm design and analysis; Bandwidth; Computational modeling; Fourier transforms; Image reconstruction; Image resolution; Instruments; Parametric statistics; Performance analysis; Reconstruction algorithms; Signal reconstruction; Signal resolution; Spatial resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.115587

Filename

115587