Super-resolution image restoration from blurred observations

Author

Bose, Nirmal K. ; Ng, Michael K. ; Yau, Andy C.

Author_Institution

Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA, USA

fYear

2005

fDate

23-26 May 2005

Firstpage

6296

Abstract

We study the problem of the reconstruction of a high-resolution image from several blurred low-resolution image frames. The image frames consist of blurred, decimated and noisy versions of a high-resolution image. The high-resolution image is modeled as a Markov random field (MRF), and a maximum a posteriori (MAP) estimation technique is used for the restoration. We show that, with the periodic boundary condition, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore high-resolution images in the aperiodic boundary condition.

Keywords

Markov processes; conjugate gradient methods; fast Fourier transforms; image resolution; image restoration; maximum likelihood estimation; MAP estimation; Markov random field; aperiodic boundary condition; blurred image; blurred observations; decimated image; fast Fourier transforms; high-resolution image reconstruction; maximum a posteriori estimation; multidimensional systems; noisy image; periodic boundary condition; preconditioned conjugate gradient method; super-resolution image restoration; Boundary conditions; Digital cameras; Fast Fourier transforms; Gradient methods; Image reconstruction; Image resolution; Image restoration; Remote monitoring; Sensor arrays; Signal resolution; high-resolution; image restoration; preconditioned conjugate gradient method; regularization;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on

Print_ISBN

0-7803-8834-8

Type

conf

DOI

10.1109/ISCAS.2005.1466080

Filename

1466080