Physical Filtering of Polarization-Encoded Images by Peano-Hilbert Fractal Path
In the framework of Stokes parameters imaging, polarization-encoded images have four channels. The relevant of such multidimensional structure comes from the set of physical information they carry about the local nature of the target. However, the noise that affects the intensity measurement may induce the no physical character of Stokes parameters and make awkward their analysis and processing. In this paper a new method to filter the additive noise of polarimetric measurement is introduced. This method is based on two multispectral filtering methods combined with a transformation of the Stokes channels following a fractal path. Using a regularization parameter, the proposed algorithm is a tradeoff between the filtering of polarization-encoded images and the preserving of their physical content. The statistical performances of the method are tested on simulated and real images using Bootstrap re-sampling.
filtering fractal path polarimetric images gaussian noise scatter plot data masking multispectral images