E5758B65-5BE8-4B15-BE40EB3388E8D019_articleThe Computational Photography Lab at Northwestern University develops imaging and display systems that combine a creative use of optical devices, sensor technology, and image processing algorithms to enable new functionality in cameras and displays. Our research is focused in the following areas:

  • Computational Imaging for leveraging novel optical designs and image processing together to enable new capabilities in conventional cameras, such as extended depth-of-field, digital refocusing, super-resolution, and measuring high dimensional appearance.
  • Computer Vision for measuring depth or spectral characteristics that inform a higher-level understanding about a scene, such as geometry or material properties.
  • Computational Displays for displaying images with an unprecedented sense of realism by allowing viewers to observe the appearance of objects in a natural and intuitive manner.



We are always looking for exceptional researchers to join our group with interest and experience in any of the following areas:

Computational cameras:

  • High dynamic range capture
  • Light field / camera array / multi-aperture imaging
  • Extended DOF imaging (e.g. focal sweep, wavefront coding)
  • Depth imaging (e.g. using focus / defocus, stereo, holography)
  • Hyperspectral / multispectral imaging
  • High resolution and super-resolution imaging (e.g. spatial, temporal, depth, spectral)
  • High-dimensional appearance / material capture (e.g. BRDF, 6D/8D reflectance)

Image processing:

  • Motion / defocus deblurring
  • Tomographic reconstruction
  • Image priors and regularization
  • Compressed sensing / sparse representations / convex optimization
  • Material recognition from hyperspectral data
  • Noise analysis of computational cameras
  • Image quality metrics for computational cameras

Camera engineering:

  • Camera design with exotic optical elements (e.g. coded aperture, lens array, diffuser, hologram)
  • Programmable imaging with DMD, LCD, custom sensor, etc.
  • Programmable imaging with mechanical motion (e.g. actuators, deformable lenses)
  • Computational correction of lens aberrations

Computational display / projection:

  • Autostereo 3D Display (e.g. light field, holographic)
  • Computational illumination / structured light / light transport analysis

Computer vision and machine learning:

  • Learning efficient data models for appearance (e.g. dictionary learning)
  • Detection, recognition, segmentation, and tracking

Scientific and Medical Applications:

  • Computational Microscopy and Biological Imaging
  • X-Ray Imaging
  • Remote sensing

Please send inquiries to: ollie(Replace this parenthesis with the @ sign)eecs.northwestern.edu