PI: Zhu LI

The goals of this project are (1) to make new end to end image processing pipeline that performs the extremely low light image denoising and enhancement task and (2) to develop a recognition friendly super resolution method for low resolution image recognition.

The project will utilize the following methodology:

• Directly processing sensor field data
• Learning based amplification of the dark
  image
• New residual learning based network for
  image denoising
• Recovering super resolved gradient
  images at multiple scales to recover
  more information useful for high level
  vision tasks
• CNN based super resolution networks
  to predict up scaled difference of
  Gaussian DoG images
• Adapting the trained models to drive a
  widely adopted key point algorithm for
  image recognition