LAUSR

Colored coded aperture optimization in compressive spectral imaging is discussed. Based on the analysis of the coherence of the underlying sensing matrix, a general family of codes is derived. These designs lead to reconstructions of multispectral scenes of better quality than the ones obtained using the traditional random black and white coded apertures. The approach used in this work exploits the structure of the sensing matrices and reduces the problem of the design of a large-scale matrix to a subset of substantially smaller problems for which it is possible to obtain a closed form solution, leading to fast design algorithms.