Demosaicking Using a Spatial Reference Image for an Anti-Aliasing Multispectral Filter Array.

Abstract

Multispectral imaging with a multispectral filter array (MSFA) facilitates snapshot imaging; however, a demosaicking process is required to estimate a fully defined multispectral image based on undersampled sensor data. Undersampling induces aliasing and adverse artifacts in the reconstructed image. To solve this problem, Jia et al. proposed the Fourier spectral filter array (FSFA), which can reduce aliasing. In this paper, we analyze the FSFA and a more generalized anti-aliasing MSFA, and we identify the property that makes MSFAs anti-aliasing. Furthermore, we propose a novel demosaicking method that is a hybrid of frequency-decomposition-based and compressive-sensing-based demosaicking. Anti-aliasing MSFAs enable demosaicking to comprehend the precise spatial structures of an image. The image assists our proposed method in precisely reconstructing images using compressive sensing. Our experimental results demonstrated that the proposed method performs better than the existing demosaicking methods, especially in terms of spatial reconstruction.