Information optimal scalable compressive imager demonstrator

Ronan Kerviche, Nan Zhu, Amit Ashok

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

5 Scopus citations

Abstract

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.
Pages2177-2179
Number of pages3
ISBN (Print)9781479957514
DOIs
StatePublished - Jan 28 2014

Keywords

  • Compressed Imaging
  • Mutual Information
  • PLE-MMSE

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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    Kerviche, R., Zhu, N., & Ashok, A. (2014). Information optimal scalable compressive imager demonstrator. In 2014 IEEE International Conference on Image Processing, ICIP 2014 (pp. 2177-2179). [7025439] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIP.2014.7025439