  While design of high performance lenses and image sensors has long been the
focus of camera development, the size, weight and power of image data
processing components is currently the primary barrier to radical improvements
in camera resolution. Here we show that Deep-Learning- Aided Compressive
Sampling (DLACS) can reduce operating power on camera-head electronics by 20x.
Traditional compressive sampling has to date been primarily applied in the
physical sensor layer, we show here that with aid from deep learning
algorithms, compressive sampling offers unique power management advantages in
digital layer compression.
