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Markov speckle for efficient random bit generation
Author(s) -
Roarke Horstmeyer,
Richard Y. Chen,
Benjamin Judkewitz,
Changhuei Yang
Publication year - 2012
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.20.026394
Subject(s) - speckle pattern , speckle noise , markov random field , computer science , markov chain , optics , markov process , image quality , cauchy distribution , artificial intelligence , algorithm , physics , segmentation , image segmentation , mathematics , image (mathematics) , statistics , machine learning
Optical speckle is commonly observed in measurements using coherent radiation. While lacking experimental validation, previous work has often assumed that speckle's random spatial pattern follows a Markov process. Here, we present a derivation and experimental confirmation of conditions under which this assumption holds true. We demonstrate that a detected speckle field can be designed to obey the first-order Markov property by using a Cauchy attenuation mask to modulate scattered light. Creating Markov speckle enables the development of more accurate and efficient image post-processing algorithms, with applications including improved de-noising, segmentation and super-resolution. To show its versatility, we use the Cauchy mask to maximize the entropy of a detected speckle field with fixed average speckle size, allowing cryptographic applications to extract a maximum number of useful random bits from speckle images.

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