Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/146603
Title: Patch-based holographic image sensing
Authors: Bruckstein, Alfred Marcel
Ezerman, Martianus Frederic
Fahreza, Adamas Aqsa
Ling, San
Keywords: Science::Mathematics
Engineering::Computer science and engineering
Issue Date: 2021
Source: Bruckstein, A. M., Ezerman, M. F., Fahreza, A. A., & Ling, S. (2021). Patch-based holographic image sensing. SIAM Journal on Imaging Sciences, 14(1), 198–223. doi:10.1137/20M1324041
Project: NRF2015-NRF-ISF001-2597
Nanyang Technological University grant M4080456
Journal: SIAM Journal on Imaging Sciences
Abstract: Holographic representations of data enable distributed storage with progressive refinement when the stored packets of data are made available in any arbitrary order. In this paper, we propose and test patch-based transform coding holographic sensing of image data. Our proposal is optimized for progressive recovery under random order of retrieval of the stored data. The coding of the image patches relies on the design of distributed projections ensuring best image recovery, in terms of the $\ell_2$ norm, at each retrieval stage. The performance depends only on the number of data packets that has been retrieved thus far. Several possible options to enhance the quality of the recovery while changing the size and number of data packets are discussed and tested. This leads us to examine several interesting bit-allocation and rate-distortion trade offs, highlighted for a set of natural images with ensemble estimated statistical properties.
URI: https://hdl.handle.net/10356/146603
ISSN: 1936-4954
DOI: 10.1137/20M1324041
DOI (Related Dataset): 10.21979/N9/V9AVLN
Schools: School of Physical and Mathematical Sciences 
Organisations: Technion
Departments: Mathematical Sciences
Rights: © 2021 Society for Industrial and Applied Mathematics (SIAM). All rights reserved. This paper was published in SIAM Journal on Imaging Sciences and is made available with permission of Society for Industrial and Applied Mathematics (SIAM).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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