@inproceedings{1149360024d14675995c9d3e2b7a02cc,
title = "Hurdles in the implementation of compressive sensing for imaging and ways to overcome them",
abstract = "The theory of compressive sensing (CS) has opened up new opportunities in the field of imaging. However, its implementation in this field is often not straight-forward and the optical imaging system engineer encounters several hurdles on the way of compressive imaging (CI) realization. The principles of CI design may differ drastically from the principles used for conventional imaging. Analytical tools developed for conventional imaging may not be optimal for compressive imaging. Nor are the conventional imaging components. Therefore often the CI designer needs to develop new tools, and imaging schemes. In this paper we overview the main challenges that might arise in the design of compressive imaging systems. The challenges are demonstrated through four tasks and systems: compressive two dimensional (2D) imager, compressive motion detection, compressive spectral imaging and compressive holography.",
keywords = "Compressive imaging, Compressive sensing, Holography, Spectral imaging",
author = "Adrian Stern and August, {Isaac Y.} and Yaniv Oiknine",
note = "Publisher Copyright: {\"i}¿½ 2016 SPIE.; Computational Imaging ; Conference date: 17-04-2016 Through 18-04-2016",
year = "2016",
month = jan,
day = "1",
doi = "https://doi.org/10.1117/12.2224702",
language = "American English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Kubala, {Kenneth S.} and Lei Tian and Abhijit Mahalanobis and Amit Ashok and Petruccelli, {Jonathan C.}",
booktitle = "Computational Imaging",
address = "United States",
}