  We consider the problem of reconstructing an image from compressive
measurements using a multi-resolution grid. In this context, the reconstructed
image is divided into multiple regions, each one with a different resolution.
This problem arises in situations where the image to reconstruct contains a
certain region of interest (RoI) that is more important than the rest. Through
a theoretical analysis and simulation experiments we show that the
multi-resolution reconstruction provides a higher quality of the RoI compared
to the traditional single-resolution approach.
