Document Type

Article

Publication Date

9-2004

Publication Source

IEEE Transactions on Image Processing

Abstract

This paper presents a novel maximum a posteriori (MAP) estimator for enhancing the spatial resolution of an image using co-registered high spatial-resolution imagery from an auxiliary sensor. Here we focus on the use of high-resolution panchomatic data to enhance hyperspectral imagery. However, the estimation framework developed allows for any number of spectral bands in the primary and auxiliary image. The proposed technique is suitable for applications where some correlation, either localized or global, exists between the auxiliary image and the image being enhanced. To exploit localized correlations, a spatially varying statistical model, based on vector quantization, is used. Another important aspect of the proposed algorithm is that it allows for the use of an accurate observation model relating the “true” scene with the low-resolutions observations. Experimental results with hyperspectral data derived from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) are presented to demonstrate the efficacy of the proposed estimator.

Inclusive pages

1174-1184

ISBN/ISSN

1057-7149

Document Version

Postprint

Comments

The document available for download is the authors' accepted manuscript, provided in compliance with publisher policies on self-archiving and with author permission; permission documentation is on file.

Publisher

Institute of Electrical and Electronics Engineers

Volume

13

Peer Reviewed

yes

Keywords

Hyperspectral, Multispectral, MAP estimation, Resolution Enhancement, Multisensor, Panchromatic Sharpening

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