Image Reconstruction in the Gigavision Camera
Abstract
The main feature of this camera is that the pixels have a binary response. The response function
of a gigavision sensor is non-linear and similar to a
logarithmic function, which makes the camera suitable for
high dynamic range imaging. Since the sensor can detect a
single photon, the camera is very sensitive and can be used
for night vision and astronomical imaging.
One important aspect of the gigavision camera is how
to estimate the light intensity through binary observations.
We model the light intensity field as 2D piecewise constant
and use Maximum Penalized Likelihood Estimation
(MPLE) to recover it. Dynamic programming is used to
solve the optimization problem. Due to the complex computation
of dynamic programming, greedy algorithm and
pruning quadtrees are proposed. They show acceptable reconstruction
performance with low computational complexity.
Experimental results with synthesized images and real
images taken by a single-photon avalanche diode (SPAD)
camera are given.
of a gigavision sensor is non-linear and similar to a
logarithmic function, which makes the camera suitable for
high dynamic range imaging. Since the sensor can detect a
single photon, the camera is very sensitive and can be used
for night vision and astronomical imaging.
One important aspect of the gigavision camera is how
to estimate the light intensity through binary observations.
We model the light intensity field as 2D piecewise constant
and use Maximum Penalized Likelihood Estimation
(MPLE) to recover it. Dynamic programming is used to
solve the optimization problem. Due to the complex computation
of dynamic programming, greedy algorithm and
pruning quadtrees are proposed. They show acceptable reconstruction
performance with low computational complexity.
Experimental results with synthesized images and real
images taken by a single-photon avalanche diode (SPAD)
camera are given.
Research Areas
