Stochastic super-resolution of satellite-based Sea Surface Temperature using conditional SPDE models

This paper addresses the simulation of high-resolution geophysical fields from low-resolution satellite observations in the context of the remote sensing of the ocean surface. Within a super-resolution framework, we investigate texture-based stochastic models while controlling high-resolution spectral, geometrical and statistical features. We introduce a novel model stated as the solution of a SPDE (Stochastic Partial Differential Equation) associated with conditional 2D Gaussian field. We address both model parameter inference from real high-resolution images and simulation issues. Experiments for Sea Surface Temperature fields demonstrate the relevance of our model compared to classical stationary schemes.