Light Field Superresolution

To be presented at ICCP 2009

Tom Bishop   Sara Zanetti   Paolo Favaro

Computer Vision Laboratory
Heriot-Watt University

Light field View extracted form the image captured Depth map Image superresolved

[Light field image]

[Light field (left) rearranged as multiple views]

[Central view extracted from the light field]

[Central view superresolved]


Light field cameras have been recently shown to be very effective in applications such as digital refocusing and 3D reconstruction. In a single snapshot these cameras provide a sample of the light field of a scene by trading off spatial resolution with angular resolution. Current methods produce images at a resolution that is much lower than that of traditional imaging devices. However, by explicitly modeling the image formation process and incorporating priors such as Lambertianity and texture statistics, these types of images can be reconstructed at a higher resolution. We formulate this method in a variational Bayesian framework and perform the reconstruction of both the surface of the scene and the (superresolved) light field. The method is demonstrated on both synthetic and real images captured with our light-field camera prototype.


Related work


We wish to thank Mohammad Taghizadeh and the diffractive optics group at Heriot-Watt University for providing us with the microlens arrays and for stimulating discussions, and Mark Stewart for designing and building our microlens array interface. This work has been supported by EPSRC grant EP/F023073/1(P).

Last update: January 26 2009