Hyperspectral Detector Correction Using Spectral Match Replacement
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Solution Overview
Problem
Hyperspectral detectors with failed detectors produce inconsistent spectral responses, leading to unreliable data that causes false alarms in downstream analytics and cannot be adequately corrected by traditional interpolation methods.
Innovation Solution
A technique that searches for a regional spectral match within a neighborhood of the failed detector to replace the inconsistent data, preserving spectral angle and magnitude by normalizing the copied radiance values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional interpolation methods (1D or 2D) are used to correct failed detector data, then the visible image product quality is improved, but spectral consistency is lost causing false alarms in downstream analytics
Solution Approach 1:
The patent copies spectral data from a reference detector (spatial or spectral neighbor) to replace the failed detector's inconsistent spectral response. This copying approach preserves the spectral characteristics needed for reliable downstream analytics while providing a complete data set for image formation.
Solution Approach 2:
The patent introduces a reference detector as an intermediary to mediate between the failed detector and the required spectral data. The reference detector serves as a proxy that provides consistent spectral information without being the original failed detector, thereby maintaining spectral fidelity.
2Reliability
If failed detector data is not corrected, then spectral consistency is maintained, but false alarms occur in downstream automated analytics
Solution Approach 1:
The patent converts the harmful effect of failed detectors (inconsistent spectral responses causing false alarms) into a beneficial outcome by systematically replacing them with data from reliable reference detectors. This transformation eliminates false alarms while preserving the detection capability through the use of validated reference data.
3Loss of information
If spectral data from failed detectors is replaced without preserving spectral angle, then data completeness is improved, but spectral accuracy deteriorates
Solution Approach 1:
The patent changes the approach from simple intensity interpolation to spectral angle-preserving replacement. By maintaining the spectral angle (angular relationship in spectral space) during data replacement, the method preserves the directional information critical for spectral accuracy while ensuring data completeness through systematic replacement of failed detector values.
Data Source
AI summary
Systems, devices, methods, and computer-readable media for improved hyperspectral images are provided. A method includes determining first pixel data of a first frequency band of frequency bands of a pixel of a hyperspectral image corresponds to a failed detector, determining a neighboring pixel of neighboring pixels of the pixel that has a corresponding first spectral profile (i) most similar to a second spectral profile of the pixel and (ii) corresponds to a non-failed detector, determining second pixel data from the first spectral profile, and replacing the first pixel data with second pixel data in the second spectral profile.


