  Event or Neuromorphic cameras are novel biologically inspired sensors that
record data based on the change in light intensity at each pixel
asynchronously. They have a temporal resolution of microseconds. This is useful
for scenes with fast moving objects that can cause motion blur in traditional
cameras, which record the average light intensity over an exposure time for
each pixel synchronously. This paper presents a bilevel inverse problem
framework for neuromorphic imaging. Existence of solution to the inverse
problem is established. Second order sufficient conditions are derived under
special situations for this nonconvex problem. A second order Newton type
solver is derived to solve the problem. The efficacy of the approach is shown
on several examples.

Optimization and Control