Spatial resolution enhancement of Earth observation products using an acceleration technique for iterative methods

A simple innovation that enables a faster convergence rate of iterative gradient-like descent approaches is proposed and applied to linear image reconstruction problems from irregular sampling. The key idea is to reduce the amount of regularization effects of the conventional Tikhonov functional by introducing a negative seminorm penalty term, whose role is to speed up the convergence without reducing the reconstruction accuracy. The method is employed to enhance the spatial resolution of microwave remotely sensed products. First experiments, undertaken on simulated radiometer data, demonstrate that the technique significantly increases the convergence rate, halving the number of iterations when applied to speed up the basic and widely used Landweber method.