An efficient wavelet-based algorithm for image superresolution

Author

Nguyen, Nhat ; Milanfar, Peyman

Author_Institution

Scientific Comput. & Comput. Math. Program, Stanford, CA, USA

Volume

2

fYear

2000

fDate

10-13 Sept. 2000

Firstpage

351

Abstract

Superresolution produces high quality, high resolution images from a set of degraded, low resolution frames. We present a new and efficient wavelet-based algorithm for image superresolution. The algorithm is a combination of interpolation and restoration processes. Unlike previous work, our method exploits the interlaced sampling structure in the low resolution data. Numerical experiments and analysis demonstrate the effectiveness of our approach and illustrate why the computational complexity only doubles for 2-D superresolution versus 1-D case.

Keywords

computational complexity; image resolution; image restoration; image sampling; interpolation; wavelet transforms; 1D superresolution; 2D superresolution; computational complexity; degraded low resolution frames; efficient wavelet-based algorithm; high quality images; high resolution images; image superresolution; interlaced sampling structure; interpolation; low resolution data; restoration; Additive noise; Degradation; Image resolution; Image restoration; Image sampling; Interpolation; Mathematics; Pixel; Scientific computing; Spatial resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2000. Proceedings. 2000 International Conference on

Conference_Location

Vancouver, BC, Canada

ISSN

1522-4880

Print_ISBN

0-7803-6297-7

Type

conf

DOI

10.1109/ICIP.2000.899387

Filename

899387