8 May 2018 Comparison of bad pixel replacement techniques for LWIR hyperspectral imagery
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Abstract
This paper compares four different bad pixel replacement algorithms for LWIR hyperspectral imagery representing both physics-based unmixing and statistics-based methods. Testing is performed on a measured dataset using detection performance as a comparison metric and synthetic dataset with reconstruction error and detection performance used to compare. It is found that a statistics-based covariance matched filter method generally performs best of the four methods tested but at significantly greater computational cost. A simple plate metaphor interpolation is the fastest technique but struggles to correct pixels where sharp spectral or spatial difference are present. Meanwhile, an endmember-based unmixing approach provided a balance between the two in terms of computational complextity and reconstruction performance.
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Jacob A. Martin, Jacob A. Martin, Genesis Islas, Genesis Islas, } "Comparison of bad pixel replacement techniques for LWIR hyperspectral imagery", Proc. SPIE 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, 106440V (8 May 2018); doi: 10.1117/12.2303508; https://doi.org/10.1117/12.2303508
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