An iterative thresholding algorithm for linear inverse problems with a sparsity constraint

Abstract We consider linear inverse problems where the solution is assumed to have a sparse expansion on an arbitrary preassigned orthonormal basis. We prove that replacing the usual quadratic regularizing penalties by weighted 𝓁 p ‐penalties on the coefficients of such expansions, with 1 ≤ p ≤ 2, ... View More