Sparsity based interferometric imaging

Abstract

Correlative interferometric imaging relies on reconstructing object intensity by using the cross-correlation across distant sensor measurements. While Fourier inversion is commonly used, the problem can also be cast as a constrained optimization problem involving positivity and boundary constraints. This paper replaces the boundary constraint with a 1 norm constraint that is known to induce sparsity under certain conditions. An experimental example demonstrates that such constrained optimization can potentially provide reconstruction whose extent conforms closely to that of the source.