Regularization destriping of remote sensing imagery
Journal Article - Open Access
Clarkson University Potsdam United States
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We illustrate the utility of variational destriping for ocean color images from both multispectral and hyperspectral sensors. In particular, we examine data from a filter spectrometer, the Visible Infrared Imaging Radiometer SuiteVIIRS on the Suomi National Polar Partnership NPPorbiter, and an airborne grating spectrometer, the Jet Population Laboratorys JPL hyperspectral Portable Remote Imaging Spectrometer PRISM sensor. We solve the destriping problem using a variational regularization method by giving weights spatially to preserve the other features of the image during the destriping process. The target functional penalizes the neighborhood of stripes strictly, directionally uniform features while promoting data fidelity, and the functional is minimized by solving the EulerLagrange equations with an explicit finite-difference scheme. We show the accuracy of our method from a benchmark data set which represents the sea surface temperature off the coast of Oregon, USA. Technical details, such as how to impose continuity across data gaps using in painting, are also described.
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