FlatCam: Replacing Lenses with Masks and Computation

M. Salman Asif, Ali Ayremlou, Ashok Veeraraghavan, Richard Baraniuk, Aswin Sankaranarayanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations

Abstract

We present a thin form-factor lensless camera, FlatCam, that consists of a coded mask placed on top of a bare, conventional sensor array. FlatCam is an instance of a coded aperture imaging system in which each pixel records a linear combination of light from multiple scene elements. A computational algorithm is then used to demultiplex the recorded measurements and reconstruct an image of the scene. In contrast with vast majority of coded aperture systems, we place the coded mask extremely close to the image sensor that can enable a thin system. We use a separable mask to ensure that both calibration and image reconstruction are scalable in terms of memory requirements and computational complexity. We demonstrate the potential of our design using a prototype camera built using commercially available sensor and mask.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Conference on Computer Vision Workshops, ICCVW 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages663-666
Number of pages4
ISBN (Electronic)9781467383905
DOIs
StatePublished - Feb 11 2016
Event15th IEEE International Conference on Computer Vision Workshops, ICCVW 2015 - Santiago, Chile
Duration: Dec 11 2015Dec 18 2015

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
Volume2016-February
ISSN (Print)1550-5499

Other

Other15th IEEE International Conference on Computer Vision Workshops, ICCVW 2015
CountryChile
CitySantiago
Period12/11/1512/18/15

Keywords

  • Apertures
  • Calibration
  • Cameras
  • Image reconstruction
  • Lenses
  • Prototypes

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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