Coded aperture design in compressive spectral imaging based on side information.

Abstract

Coded aperture compressive spectral imagers (CSI) sense a three-dimensional data cube by using two-dimensional projections of the coded and spectrally dispersed input image. Recently, it has been shown that by combining spectral images acquired from a CSI sensor and a complementary sensor leads to substantial improvement in the quality of the fused image. To maximally exploit the benefits of the complementary information, the spatial structure of the coded apertures must be optimized inasmuch as these structures determine the sensing matrix properties and, accordingly, the quality of the reconstructed images. This paper proposes a method to use side information from a red-green-blue sensor to design the coded aperture patterns of a CSI imager, such that more detailed spatial images and wavelength profiles can be reconstructed. The side information is used as the input of an edge detection algorithm to approximate a version of the edges of the spectral images. The coded apertures are designed to follow the spatial structure determined by the estimated spectral edges, such that the high frequencies are promoted, leading to more detailed reconstructed spectral images. Simulations and experimental results indicate that when compared with random coded aperture structures, the designed coded apertures based on side information obtain up to 3dB improvement in the quality of the reconstructed images.