Paper
3 September 2008 Superresolution image reconstruction using panchromatic and multispectral image fusion
M. I. Elbakary, M. S. Alam
Author Affiliations +
Abstract
Hyperspectral imagery is used for a wide variety of applications, including target detection, tacking, agricultural monitoring and natural resources exploration. The main reason for using hyperspectral imagery is that these images reveal spectral information about the scene that is not available in a single band. Unfortunately, many factors such as sensor noise and atmospheric scattering degrade the spatial quality of these images. Recently, many algorithms are introduced in the literature to improve the resolution of hyperspectral images using co-registered high special-resolution imagery such as panchromatic imagery. In this paper, we propose a new algorithm to enhance the spatial resolution of low resolution hyperspectral bands using strongly correlated and co-registered high special-resolution panchromatic imagery. The proposed algorithm constructs the superresolution bands corresponding to the low resolution bands to enhance the resolution using a global correlation enhancement technique. The global enhancement is based on the least square regression and the histogram matching to improve the estimated interpolation of the spatial resolution. The introduced algorithm is considered as an improvement for Price’s algorithm which uses the global correlation only for the spatial resolution enhancement. Numerous studies are conducted to investigate the effect of the proposed algorithm for achieving the enhancement compared to the traditional algorithm for superresolution enhancement. Experiments results obtained using hyperspectral data derived from airborne imaging sensor are presented to verify the superiority of the proposed algorithm.
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M. I. Elbakary and M. S. Alam "Superresolution image reconstruction using panchromatic and multispectral image fusion", Proc. SPIE 7072, Optics and Photonics for Information Processing II, 70721N (3 September 2008); https://doi.org/10.1117/12.804166
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KEYWORDS
Spatial resolution

Image resolution

Resolution enhancement technologies

Hyperspectral imaging

Algorithm development

Super resolution

Data modeling

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