Quasi-Monte Carlo: halftoning in high dimensions?

Kenneth M. Hanson

doi:10.1117/12.484808

1 July 2003 Quasi-Monte Carlo: halftoning in high dimensions?

Kenneth M. Hanson

Proceedings Volume 5016, Computational Imaging; (2003) https://doi.org/10.1117/12.484808
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

The goal in Quasi-Monte Carlo (QMC) is to improve the accuracy of integrals estimated by the Monte Carlo technique through a suitable specification of the sample point set. Indeed, the errors from N samples typically drop as N^-1 with QMC, which is much better than the N^-1/2 dependence obtained with Monte Carlo estimates based on random point sets. The heuristic reasoning behind selecting QMC point sets is similar to that in halftoning (HT), that is, to spread the points out as evenly as possible, consistent with the desired point density. I will outline the parallels between QMC and HT, and describe an HT-inspired algorithm for generating a sample set with uniform density, which yields smaller integration errors than standard QMC algorithms in two dimensions.

Citation Download Citation

Kenneth M. Hanson "Quasi-Monte Carlo: halftoning in high dimensions?", Proc. SPIE 5016, Computational Imaging, (1 July 2003); https://doi.org/10.1117/12.484808

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available