High-dynamic range compressive spectral imaging by grayscale coded aperture adaptive filtering

Abstract

The coded aperture snapshot spectral imaging system (CASSI) is an imaging architecture which senses the three dimensional informa-tion of a scene with two dimensional (2D) focal plane array (FPA) coded projection measurements. A reconstruction algorithm takes advantage of the compressive measurements sparsity to recover the underlying 3D data cube. Traditionally, CASSI uses block-un-block coded apertures (BCA) to spatially modulate the light. In CASSI the quality of the reconstructed images depends on the design of these coded apertures and the FPA dynamic range. This work presents a new CASSI architecture based on grayscaled coded apertu-res (GCA) which reduce the FPA saturation and increase the dynamic range of the reconstructed images. The set of GCA is calculated in a real-time adaptive manner exploiting the information from the FPA compressive measurements. Extensive simulations show the attained improvement in the quality of the reconstructed images when GCA are employed. In addition, a comparison between traditional coded apertures and GCA is realized with respect to noise tolerance.

Keywords

• Compressive sensing
• hyperspectral imaging
• saturation
• dynamic range
• coded aperture
• optical imaging.