General demosaicking for multispectral polarization filter arrays using total generalized variation and weighted tensor nuclear norm minimization.

Abstract

We focus on a demosaicking method for recovering multispectral polarization images (MSPIs) from a single image captured by a multispectral polarization filter array (MSPFA). Since the image captured by the MSPFA can be represented by a linear model, an algorithm to solve the inverse problem can be designed to enable general-purpose demosaicking regardless of the transmission characteristics and patterns of the MSPFA. Thus, we propose a method for demosaicking MSPIs by solving an inverse problem that introduces the decorrelated vectorial total generalized variation (D-VTGV) and weighted tensor nuclear norm (WTNN) regularization functions. D-VTGV evaluates the edge-preserving property in the spatial direction while preserving the correlation between bands and polarization angles, while WTNN exploits the correlation and low-rank property in nonlocal regions of the image to perform proper texture restoration and denoising. The experimental results show that the proposed method can restore images well for both the ideal MSPFA and an MSPFA manufactured from photonic crystals.