On the noise-resolution duality, Heisenberg uncertainty and Shannon's information

Authors

  • Timur Gureyev Monash Universtiy, CSIRO, University of New England
  • Frank de Hoog CSIRO Digital Productivity
  • Yakov Nesterets CSIRO Manufacturing Flagship, University of New England
  • David Paganin Monash University

DOI:

https://doi.org/10.21914/anziamj.v56i0.9414

Keywords:

uncertainty inequalities, Heisenberg uncertainty, Shannon information, noise, spatial resolution

Abstract

Several variations of the Heisenberg uncertainty inequality are derived on the basis of `noise-resolution duality' recently proposed by us. The same approach leads to a related inequality that provides an upper limit for the information capacity of imaging systems in terms of the number of imaging quanta (particles) used in the experiment. These results are useful in the context of biomedical imaging constrained by the radiation dose delivered to the sample, or in imaging (e.g., astronomical) problems under low light conditions. References
  • R. Bach, D. Pope, S.-H. Liou and H. Batelaan, Controlled double-slit electron diffraction. New J. Phys. 15:033018, 2013. doi:10.1088/1367-2630/15/3/033018
  • H. H. Barrett and K. J. Myers, Foundations of image science. Wiley, Hoboken, 2004. http://au.wiley.com/WileyCDA/WileyTitle/productCd-0471153001.html
  • H. Bateman and A. Erdelyi, Tables of integral transforms. McGraw–Hill, New York, 1954. http://resolver.caltech.edu/CaltechAUTHORS:20140123-101456353
  • M. Born and E. Wolf, Principles of optics. Cambridge University Press, Cambridge, 1999. doi:10.1017/CBO9781139644181
  • I. J. Cox and C. J. R. Sheppard, Information capacity and resolution in an optical system. J. Opt. Soc. Am. A 3:1152–1158, 1986. doi:10.1364/JOSAA.3.001152
  • M. G. Cowling and J. F. Price, Bandwidth versus time concentration: the Heisenberg–Pauli–Weyl inequality. SIAM J. Math. Anal. 15(1):151–165, 1984. doi:10.1137/0515012
  • F. de Hoog, G. Schmalz and T. E. Gureyev, An uncertainty inequality. Appl. Math. Lett. 38:84–86, 2014. doi:10.1016/j.aml.2014.07.009
  • I. Dreier, W. Ehm, T. Gneiting and D. Richards, Improved bounds for Laue's constant and multivariate extensions. Math. Nachr. 228:109–122, 2001. doi:10.1002/1522-2616(200108)228:1<109::AID-MANA109>3.0.CO;2-V
  • V. A. Epanechnikov, Non-parametric estimation of a multivariate probability density. Theor. Probab. Appl. 14:153–158, 1969. doi:10.1137/1114019
  • A. C. Fabian, K. A. Pounds and R. D. Blandford, Frontiers of x-ray astronomy. Cambridge University Press, Cambridge, 2004.
  • P. B. Felgett and E. H. Linfoot, On the assessment of optical images. Phil. T. R. Soc. A 247:369–407, 1955. doi:10.1098/rsta.1955.0001
  • G. B. Folland and A. Sitaram, The uncertainty principle: a mathematical survey. J. Fourier Anal. Appl. 3:207–238, 1997. doi:10.1007/BF02649110
  • T. E. Gureyev, Ya. I. Nesterets, F. de Hoog, G. Schmalz, S. C. Mayo, S. Mohammadi and G. Tromba, Duality between noise and spatial resolution in linear systems. Opt. Express 22:9087–9094, 2014. doi:10.1364/OE.22.009087
  • T. E. Gureyev, S. C. Mayo, Ya. I. Nesterets, S. Mohammadi, D. Lockie, R. H. Menk, F. Arfelli, K. M. Pavlov, M. J. Kitchen, F. Zanconati, C. Dullin and G. Tromba, Investigation of imaging quality of synchrotron-based phase-contrast mammographic tomography. J. Phys. D: Appl. Phys. 47:365401, 2014. doi:10.1088/0022-3727/47/36/365401
  • M. R. Howells, T. Beetz, H. N. Chapman, C. Cui, J. M. Holton, C. J. Jacobsen, J. Kirz, E. Lima, S. Marchesini, H. Miao, D. Sayre, D. A. Shapiro, J. C. H. Spence and D. Starodub, An assessment of the resolution limitation due to radiation-damage in x-ray diffraction microscopy. J. Electron Spectrosc. 170:4–12, 2009. doi:10.1016/j.elspec.2008.10.008
  • E. Laeng and C. Morpurgo, An uncertainty inequality involving \(L^1\) norms. P. Am. Math. Soc. 127:3565–3572, 1999. http://www.jstor.org/stable/119352
  • Ya. I. Nesterets and T. E. Gureyev, Young's double-slit experiment: noise-resolution duality. Opt. Express 23:3373–3381, 2015. doi:10.1364/OE.23.003373
  • C. Shannon: Communication in the presence of noise. P. IRE 37:10–21, 1949. doi:10.1109/JRPROC.1949.232969

Published

2015-09-30

Issue

Section

Proceedings Computational Techniques and Applications Conference