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Proceedings Paper

Landsat multispectral sharpening using a sensor system model and panchromatic image
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Paper Abstract

The thematic mapper (TM) sensor aboard Landsats 4, 5 and enhanced TM plus (ETM+) on Landsat 7 collect imagery at 30-m sample distance in six spectral bands. New with ETM+ is a 15-m panchromatic (P) band. With image sharpening techniques, this higher resolution P data, or as an alternative, the 10-m (or 5-m) P data of the SPOT satellite, can increase the spatial resolution of the multispectral (MS) data. Sharpening requires that the lower resolution MS image be coregistered and resampled to the P data before high spatial frequency information is transferred to the MS data. For visual interpretation and machine classification tasks, it is important that the sharpened data preserve the spectral characteristics of the original low resolution data. A technique was developed for sharpening (in this case, 3:1 spatial resolution enhancement) visible spectral band data, based on a model of the sensor system point spread function (PSF) in order to maintain spectral fidelity. It combines high-pass (HP) filter sharpening methods with iterative image restoration to reduce degradations caused by sensor-system-induced blurring and resembling. Also there is a spectral fidelity requirement: sharpened MS when filtered by the modeled degradations should reproduce the low resolution source MS. Quantitative evaluation of sharpening performance was made by using simulated low resolution data generated from digital color-IR aerial photography. In comparison to the HP-filter-based sharpening method, results for the technique in this paper with simulated data show improved spectral fidelity. Preliminary results with TM 30-m visible band data sharpened with simulated 10-m panchromatic data are promising but require further study.

Paper Details

Date Published: 8 August 2003
PDF: 12 pages
Proc. SPIE 5108, Visual Information Processing XII, (8 August 2003); doi: 10.1117/12.487262
Show Author Affiliations
George P. Lemeshewsky, U.S. Geological Survey (United States)

Published in SPIE Proceedings Vol. 5108:
Visual Information Processing XII
Zeno J. Geradts; Zia-ur Rahman; Lenny I. Rudin; Robert A. Schowengerdt; Stephen E. Reichenbach, Editor(s)

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