Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Super-resolution reconstruction algorithm to MODIS remote sensing images

Language

English

Abstract

In this paper, we propose a super-resolution image reconstruction algorithm to moderate-resolution imaging spectroradiometer (MODIS) remote sensing images. This algorithm consists of two parts: registration and reconstruction. In the registration part, a truncated quadratic cost function is used to exclude the outlier pixels, which strongly deviate from the registration model. Accurate photometric and geometric registration parameters can be obtained simultaneously. In the reconstruction part, the L1 norm data fidelity term is chosen to reduce the effects of inevitable registration error, and a Huber prior is used as regularization to preserve sharp edges in the reconstructed image. In this process, the outliers are excluded again to enhance the robustness of the algorithm. The proposed algorithm has been tested using real MODIS band-4 images, which were captured in different dates. The experimental results and comparative analyses verify the effectiveness of this algorithm. © The Author 2007. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.

Keywords

Huber prior, L1 norm data fidelity, MODIS images, Outliers, Super-resolution

Publication Date

2009

Source Publication Title

Computer Journal

Volume

52

Issue

1

Start Page

90

End Page

100

Publisher

Oxford University Press

DOI

10.1093/comjnl/bxm028

Link to Publisher's Edition

http://dx.doi.org/10.1093/comjnl/bxm028

ISSN (print)

00104620

ISSN (electronic)

14602067

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