Spectral and polarization imaging (SPI) is an emerging sensing method that permits the analysis of both spectral and polarization information of a scene. The existing acquisition systems are limited by several factors, such as the space requirement, the inability to capture quickly the information, and the high cost. We propose an SPI acquisition system with a high spatial resolution that combines six spectral channels and four polarization channels. The optical setup employs two color-polarization filter array cameras and a pair of bandpass filters. We define the processing pipeline, consisting of preprocessing, geometric calibration, spectral calibration, and data transformation. We show that, around specular highlights, the spectral reconstruction can be improved by filtering the polarized intensity. We provide a database of 28 spectropolarimetric scenes with different materials for future simulation and analysis by the research community.

A polarization filter array (PFA) camera is an imaging device capable of analyzing the polarization state of light in a snapshot manner. These cameras exhibit spatial variations, i.e., nonuniformity, in their response due to optical imperfections introduced during the nanofabrication process. Calibration is done by computational imaging algorithms to correct the data for radiometric and polarimetric errors. We reviewed existing calibration methods and applied them using a practical optical acquisition setup and a commercially available PFA camera. The goal of the evaluation is first to compare which algorithm performs better with regard to polarization error and then to investigate both the influence of the dynamic range and number of polarization angle stimuli of the training data. To our knowledge, this has not been done in previous work.