Information optimal scalable compressive imager demonstrator

Ronan Kerviche, Nan Zhu, Amit Ashok

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

6 Scopus citations


We present a compressive imager demonstrator based on a scalable, parallel architecture. It primarily utilizes information-optimal projections and a Piece-wise Linear Minimum Mean Square Error Estimator (PLE-MMSE) combined with a block-based statistical model of natural images. Such system delivers high-resolution images from low resolution sensor with near real-time snapshots. This testbed provides a highly programmable compressive imager that allows testing of a variety of projection designs for different tasks (e.g. random binary, PCA) and also enables adaptive or dynamic designs.

Original languageEnglish (US)
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages3
ISBN (Electronic)9781479957514
StatePublished - Jan 28 2014

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014


  • Compressed Imaging
  • Mutual Information

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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