In many security applications, the image being recorded is not
as important to keep track of as the difference between images.
For example, if there is a camera recording an empty back
hallway, the image being transmitted could be unchanging for
hours or even days. If that hallway needs to be secure, however,
that same image may still be constantly transmitted to a
receiver, wasting bandwidth (in the case of a wireless video
network) and power. Ideally, we would only transmit changes in
the video, but most background subtraction algorithms require
much more processing than can be accomplished on a cameras
processor. This can be accomplished with very little processing
or complexity at the transmitter, pushing all of the complexity
to the receiver. Considering most video networks already have a
PC as the receiver, this solution fits with current network
topologies. Compressed sensing is a mathematical process by
which a signal can be undersampled (below the Nyquist rate), and
recovered by using ℓ1 minimization