Compressive Spectral Imaging via Misalignment Induced Equivalent Grayscale Coded Aperture

Abstract

Coded aperture snapshot spectral imager (CASSI) senses the spectral information of a 2D scene and captures a set of coded measurement data that can be used to reconstruct the 3D spatio-spectral datacube of the input scene by compressive sensing algorithms. The coded aperture (CA) in CASSI plays a crucial role in modulating the spatial information. The pixels in CA are typically square, switched binary on-off, and aligned with the pixels of focal plane array (FPA). Instead of this binary modulation, this paper explores a simple yet effective approach to enabling an equivalent grayscale modulation, which can increase the sensing degree of freedom in CASSI systems. In particular, we deliberately introduce misalignment between the CA pixels and the FPA pixels, such that the spatial modulation of one FPA pixel is determined by four adjacent CA pixels instead of one. Numerical experiments show that the proposed equivalent grayscale modulation induced by misalignment can significantly improve the CASSI reconstruction when compared with current methods, whether a random CA or an optimal blue noise CA is used. More importantly, it does not incur in any cost to the CASSI system.