Resolution enhancement by image fusion for microgrid polarization imagers

Abstract

Microgrid polarization imaging systems inherently suffer from spatial aliasing in addition to the image degrading effects of camera blur and noise. In this paper, microgrid aliasing is reduced by a factor of two and noise is suppressed via a fast image fusion technique borrowed from the study of super resolution. Additionally, a new regularization cost function for microgrid super resolution estimators is proposed. Polarimetric image fusion results are demonstrated with laboratory data. 1 2

Super-resolution for imagery from integrated microgrid polarimeters

“…Because of their ability to help overcome undersampling, we believe multi-frame SR algorithms are a powerful match for microgrid polarimeters. To the best of our knowledge, the only publications to date exploring this connection were the result of preliminary work led by two of the current coauthors [5,6]. We believe the current paper represents the first comprehensive treatment of the subject.…”

“…In [5], Ratliff et al used the iterative multi-frame SR algorithm in [7] applied to the four demosaiced polarimetric channels independently. LeMaster explored a simple and fast multi-frame SR algorithm in [6] that registered and interlaced samples from multiple frames, also using independent channel processing. The work in [5,6] demonstrated that SR can be used to enhance the resolution of polarimetric data from a microgrid imager, but neither fully exploited the redundant information available in the microgrid array.…”