  One of the major open problems in computer vision is detection of features in
visually impaired images. In this paper, we describe a potential solution using
Phase Stretch Transform, a new computational approach for image analysis, edge
detection and resolution enhancement that is inspired by the physics of the
photonic time stretch technique. We mathematically derive the intrinsic
nonlinear transfer function and demonstrate how it leads to (1) superior
performance at low contrast levels and (2) a reconfigurable operator for
hyper-dimensional classification. We prove that the Phase Stretch Transform
equalizes the input image brightness across the range of intensities resulting
in a high dynamic range in visually impaired images. We also show further
improvement in the dynamic range by combining our method with the conventional
techniques. Finally, our results show a method for computation of mathematical
derivatives via group delay dispersion operations.
