Multiscale Optimal Filtering on the Sphere

We present a framework for the optimal filtering of spherical signals contaminated by realizations an additive, zero-mean, uncorrelated and anisotropic noise process on sphere. Filtering is performed in wavelet domain given scale-discretized transform The proposed filter sense that it minimizes mean square error between filtered representation noise-free signal. also simplified formulation case when azimuthally symmetric functions are used. demonstrate use denoising Earth topography map presence white Gaussian noise, show performs better than hard thresholding method weighted harmonic (weighted-SPHARM) signal estimation framework.