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Scene-based method for spatial misregistration detection in hyperspectral imagery
Francesco Dell'Endice1, Jens Nieke, Daniel Schläpfer
1Remote Sensing Laboratories, Department of Geography, University of Zurich, Switzerland. fradel@geo.unizh.ch
Applied Optics
|May 22, 2007
Summary
Hyperspectral imaging (HSI) sensors have spatial misregistration issues affecting spectral accuracy. A new edge-detection method quantifies this misalignment, crucial for improving HSI data quality.
Area of Science:
- Remote Sensing
- Optical Engineering
- Spectroscopy
Background:
- Hyperspectral imaging (HSI) sensors are prone to spatial misregistration, compromising spectral data integrity.
- This artifact's impact varies with spectral wavelength and across-track sensor position.
Purpose of the Study:
- To propose and validate a scene-based method for quantifying spatial misregistration in HSI sensors.
- To confirm the dependence of misregistration on wavelength and across-track position.
Main Methods:
- A novel scene-based approach utilizing edge detection techniques.
- Measurement of spatial edge variations across different monochromatic projections.
- Application to various prism- and grating-based HSI sensor designs.
Main Results:
- The proposed edge-detection method effectively estimates spatial misregistration.
- Confirmed dependence of misregistration on spectral wavelength (λ) and across-track position (θ).
- Identified misalignments in tested HSI sensors.
Conclusions:
- The developed method accurately quantifies HSI spatial misregistration.
- Findings support the wavelength and across-track dependency of this artifact.
- Provides a foundation for developing correction strategies for HSI data.
