Here is some very fast compressive sensing using coded aperture.
Conventional imaging uses a set of lenses to form an image on the sensor
plane. This pure hardware-based approach doesn't use any signal processing, nor
the extra information in the time of arrival of photons to the sensor.
Recently, modern compressive sensing techniques have been applied for lensless
imaging. However, this computational approach tends to depend as much as
possible on signal processing (for example, single pixel camera) and results in
a long acquisition time. Here we propose using compressive ultrafast sensing
for lensless imaging. We use extremely fast sensors (picosecond time
resolution) to time tag photons as they arrive to an omnidirectional pixel.
Thus, each measurement produces a time series where time is a function of the
photon source location in the scene. This allows lensless imaging with
significantly fewer measurements compared to regular single pixel imaging (33× less measurements in our experiments). To achieve this goal, we
developed a framework for using ultrafast pixels with compressive sensing,
including an algorithm for ideal sensor placement, and an algorithm for
optimized active illumination patterns. We show that efficient lensless imaging
is possible with ultrafast imaging and compressive sensing. This paves the way
for novel imaging architectures, and remote sensing in extreme situations where
imaging with a lens is not possible.
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