Compressive sensing for incoherent imaging systems with optical constraints

We consider the problem of linear projection design for incoherent optical imaging systems. We propose a computationally efficient method to obtain effective measurement kernels that satisfy the physical constraints imposed by an optical system, starting first from arbitrary kernels, including those that satisfy a less demanding power constraint. Performance is measured in terms of mutual information between the source input and the projection measurement, as well as reconstruction error for real world images. A clear improvement in the quality of image reconstructions is shown with respect to both random and adaptive projection designs in the literature.