Use of Motion Estimation Algorithms for Improved Flux Measurements Using SO 2 Cameras

摘要: abstract Article history:Received 3 April 2014Accepted 18 August 2014Available online xxxxKeywords:SO 2 fluxSO cameraPlume speedPlume modellingOptical-flowMotion estimation SO cameras are rapidly gaining popularity as a tool for monitoring emissions from volcanoes. Severaldifferent camera systems have been developed with varying patterns of image acquisition in space, timeand wavelength. Despite this diversity, there two steps common to the workflowsofmostofthesesystems;aligning images different wavelengths calculate apparent absorbance and estimating plume transportspeeds, both which can be achieved using motion algorithms. Here we present suchalgorithms,aDualTreeComplexWaveletTransform-basedalgorithmandtheFarnebackOpticalFlowalgorithm.Weassesstheiraccuracyusingasyntheticdatasetcreatedusingthenumericcloud-resolvingmodelATHAM,andthen apply them real world data Villarrica volcano. Both algorithms found perform well theATHAM simulations offer useful datasets benchmarking validating future algorithms.© 2014 The Authors. Published by Elsevier B.V. This is an open access article under CC BY license(http://creativecommons.org/licenses/by/3.0/).