A non-stationary image prior combination in super-resolution

Villena, S.; Vega, M.; Molina, R.; Katsaggelos, Aggelos

doi:10.1016/j.dsp.2014.05.017

A non-stationary image prior combination in super-resolution

Journal Article · Fri Jun 06 00:00:00 EDT 2014 · Digital Signal Processing

DOI:https://doi.org/10.1016/j.dsp.2014.05.017· OSTI ID:1488408

Villena, S. ^[1]; ^[2]; Molina, R. ^[2]; ^[3]

Univ. de Granada, Granada (Spain); Northwestern University
Univ. de Granada, Granada (Spain)
Northwestern Univ., Evanston, IL (United States)

Here, a new Bayesian Super-Resolution(SR) image registration and reconstruction method is proposed. The new method utilizes a prior distribution based on a general combination of spatially adaptive, or non-stationary, image filters, which includes an adaptive local strength parameter able to preserve both image edges and textures. With the application of variational techniques, the proposed method allows for the automatic estimation of all problem unknowns. An experimental comparison between state of the art methods and the proposed SR approach has been performed on both synthetic and real images.

Research Organization:: Northwestern Univ., Evanston, IL (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA), Office of Nonproliferation and Verification Research and Development (NA-22)

DOE Contract Number:: NA0002520

OSTI ID:: 1488408

Journal Information:: Digital Signal Processing, Journal Name: Digital Signal Processing Journal Issue: C Vol. 32; ISSN 1051-2004

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

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