Abstract
We propose two new approaches for efficiently compressing unstructured data defined on the unit sphere. Both approaches are based upon a meshfree multiscale representation of functions on the unit sphere. This multiscale representation employs compactly supported radial basis functions of different scales. The first approach is based on a simple thresholding strategy after the multiscale representation is computed. The second approach employs a dynamical discarding strategy, where small coefficients are already discarded during the computation of the approximate multiscale representation. We analyse the (additional) error which comes with either compression and provide numerical experiments using topographical data of the earth.
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Le Gia, Q., Wendland, H. Data compression on the sphere using multiscale radial basis function approximation. Adv Comput Math 40, 923–943 (2014). https://doi.org/10.1007/s10444-013-9334-z
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DOI: https://doi.org/10.1007/s10444-013-9334-z