Cookies disclaimer

I agree Our site saves small pieces of text information (cookies) on your device in order to deliver better content and for statistical purposes. You can disable the usage of cookies by changing the settings of your browser. By browsing our website without changing the browser settings you grant us permission to store that information on your device.

Third International Workshop

NONLINEAR PROCESSES IN OCEANIC AND ATMOSPHERIC FLOWS


6-8 July 2016 | ICMAT, Campus Cantoblanco UAM, Madrid, Spain



Variational Destriping on Remote Sensing Imagery



Author

Ranil Basnayake (Clarkson University). Erik Bollt (Clarkson University)


PDF version


Abstract


A commonly pronounced artifact in many remote sensing (satellite) images are stripes, mainly due to the variations of calibrations, sensor arrangement and the view angles from detector to detector. We present a destriping method by developing a functional with anisotropic smoothing transverse to the stripes, while preserving the rest of the features of the image. The destriped image is uncovered by optimizing the functional using variational methods, followed by numerical methods from finite difference approximations. We demonstrate our method on two different striped data sets (VIIRS and HICO).

A commonly pronounced artifact in many remote sensing (satellite) images are stripes, mainly due to the variations of calibrations, sensor arrangement and the view angles from detector to detector. We present a destriping method by developing a functional with anisotropic smoothing transverse to the stripes, while preserving the rest of the features of the image. The destriped image is uncovered by optimizing the functional using variational methods, followed by numerical methods from finite difference approximations. We demonstrate our method on two different striped data sets (VIIRS and HICO).