Snapshot polarization imaging has gained interest in the last few decades. Recent research and technology achievements defined the polarization Filter Array (PFA). It is dedicated to division-of-focal plane polarimeters, which permits to analyze the direction of light electric field oscillation. Its filters form a mosaicked pattern, in which each pixel only senses a fraction of the total polarization states, so the other missing polarization states have to be interpolated. As for Color or Spectral Filter Arrays (CFA or SFA), several dedicated demosaicking methods exist in the PFA literature. Such methods are mainly based on spatial correlation disregarding inter-channel correlation. We show that polarization channels are strongly correlated in images. We therefore propose to extend some demosaicking methods from CFA/SFA to PFA, and compare them with those that are PFA-oriented. Objective and subjective analysis show that the pseudo panchromatic image difference method provides the best results and can be used as benchmark for PFA demosaicking.

We present an imaging system that measures the polarimetric state of the light coming from each point of a scene. This system, which determines the four components of the Stokes vector at each spatial location, is based on a liquid-crystal polarization modulator, which makes it possible to acquire four-dimensional Stokes parameter images at a standard video rate. We show that using such polarimetric images instead of simple intensity images can improve target detection and segmentation performance.

Fabric inspection has an importance to prevent the risk of delivering inferior quality product. Until recently, the process was still undertaken offline and manually by humans, which has many drawbacks. The continuous development in computer technology introduces the automated fabric inspection as an effective alternative. In our work, Fast Fourier Transform and Cross-correlation techniques, i.e. linear operations, are first implemented to examine the structure regularity features of the fabric image in the spatial domain. To improve the efficiency of the technique and overcome the problem of detection errors, further thresholding operation is implemented using a level selection filter. Through this filter, the technique is able to detect only the actual or real defects and highlight its exact dimensions. A software package such as Matlab or Scilab is used for this procedure. It is implemented firstly on a simulated plain fabric to determine the most important parameters during the process of defect detection and then to optimize each of them even considering noise. To verify the success of the technique, it is implemented on real plain fabric samples with different colors containing various defects. Several results of the proposed technique for the simulated and real plain fabric structures with the most common defects are presented. Finally, a vision-based fabric inspection prototype that could be accomplished on-loom to inspect the fabric under construction with 100% coverage is proposed.

In the field of polarimetry, ferroelectric liquid crystal cells are mostly used as bistable polarization rotators suitable to analyze crossed polarizations. This paper shows that, provided such a cell is used at its nominal wavelength and correctly driven, its behavior is close to that of a tunable half-wave plate, and it can be used with much benefit in lightweight imaging polarimetric setups. A partial Stokes polarimeter using a single digital video camera and a single ferroelectric liquid crystal modulator is designed and implemented for linear polarization analysis. Polarization azimuthal angle and degree of linear polarization are available at 150 frames per second with a good accuracy.

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.