research-article

Stair blue noise sampling

Authors:

Bhavya Kailkhura,

Jayaraman J. Thiagarajan,

Peer-Timo Bremer,

Pramod K. VarshneyAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 35, Issue 6

Article No.: 248, Pages 1 - 10

https://doi.org/10.1145/2980179.2982435

Published: 05 December 2016 Publication History

Abstract

A common solution to reducing visible aliasing artifacts in image reconstruction is to employ sampling patterns with a blue noise power spectrum. These sampling patterns can prevent discernible artifacts by replacing them with incoherent noise. Here, we propose a new family of blue noise distributions, Stair blue noise, which is mathematically tractable and enables parameter optimization to obtain the optimal sampling distribution. Furthermore, for a given sample budget, the proposed blue noise distribution achieves a significantly larger alias-free low-frequency region compared to existing approaches, without introducing visible artifacts in the mid-frequencies. We also develop a new sample synthesis algorithm that benefits from the use of an unbiased spatial statistics estimator and efficient optimization strategies.

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Cited By

Huang XRitschel TSeidel HMemari PSingh G(2023)Patternshop: Editing Point Patterns by Image ManipulationACM Transactions on Graphics10.1145/359241842:4(1-14)Online publication date: 26-Jul-2023
https://dl.acm.org/doi/10.1145/3592418
Shan YHu DWang ZJia T(2023)Multi-channel nuclear norm minus Frobenius norm minimization for color image denoisingSignal Processing10.1016/j.sigpro.2023.108959207:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.sigpro.2023.108959
Liang ZGai JChen XMa TLiu Q(2023)A Method for Threshold Setting and False Alarm Probability Evaluation for Radar DetectorsSignal Processing10.1016/j.sigpro.2023.108930207:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.sigpro.2023.108930
Show More Cited By

Index Terms

Stair blue noise sampling
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
      1. Antialiasing
      2. Image processing
    2. Rendering

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Sampling is a core process for a variety of graphics applications. Among existing sampling methods, blue noise sampling remains popular thanks to its spatial uniformity and absence of aliasing artifacts. However, research so far has been mainly focused ...
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In this article we revisit the problem of blue noise sampling with a strong focus on the spectral properties of the sampling patterns. Starting from the observation that oscillations in the power spectrum of a sampling pattern can cause aliasing ...

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 35, Issue 6

November 2016

1045 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/2980179

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Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 05 December 2016

Published in TOG Volume 35, Issue 6

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Cited By

Huang XRitschel TSeidel HMemari PSingh G(2023)Patternshop: Editing Point Patterns by Image ManipulationACM Transactions on Graphics10.1145/359241842:4(1-14)Online publication date: 26-Jul-2023
https://dl.acm.org/doi/10.1145/3592418
Shan YHu DWang ZJia T(2023)Multi-channel nuclear norm minus Frobenius norm minimization for color image denoisingSignal Processing10.1016/j.sigpro.2023.108959207:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.sigpro.2023.108959
Liang ZGai JChen XMa TLiu Q(2023)A Method for Threshold Setting and False Alarm Probability Evaluation for Radar DetectorsSignal Processing10.1016/j.sigpro.2023.108930207:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.sigpro.2023.108930
Kouni VRauhut HTheoharis T(2023)Star DGT: a robust Gabor transform for speech denoisingSampling Theory, Signal Processing, and Data Analysis10.1007/s43670-023-00053-x21:1Online publication date: 12-Apr-2023
https://doi.org/10.1007/s43670-023-00053-x
Ahmed ARen JWonka P(2022)Gaussian Blue NoiseACM Transactions on Graphics10.1145/3550454.355551941:6(1-15)Online publication date: 30-Nov-2022
https://dl.acm.org/doi/10.1145/3550454.3555519
Peterson JBay BKoning JRobinson PSemler JWhite JAnirudh RAthey KBremer PDi Natale FFox DGaffney JJacobs SKailkhura BKustowski BLanger SSpears BThiagarajan JVan Essen BYeom J(2022)Enabling machine learning-ready HPC ensembles with MerlinFuture Generation Computer Systems10.1016/j.future.2022.01.024131(255-268)Online publication date: Jun-2022
https://doi.org/10.1016/j.future.2022.01.024
Muniraju GKailkhura BThiagarajan JBremer PTepedelenlioglu CSpanias A(2021)Coverage-Based Designs Improve Sample Mining and Hyperparameter OptimizationIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2020.298293632:3(1241-1253)Online publication date: Mar-2021
https://doi.org/10.1109/TNNLS.2020.2982936
Kailkhura BThiagarajan JLi QZhang JZhou YBremer PLarochelle HRanzato MHadsell RBalcan MLin H(2020)A statistical mechanics framework for task-agnostic sample design in machine learningProceedings of the 34th International Conference on Neural Information Processing Systems10.5555/3495724.3496724(11925-11935)Online publication date: 6-Dec-2020
https://dl.acm.org/doi/10.5555/3495724.3496724
Öztireli A(2020)A Comprehensive Theory and Variational Framework for Anti‐aliasing Sampling PatternsComputer Graphics Forum10.1111/cgf.1405939:4(133-148)Online publication date: 20-Jul-2020
https://doi.org/10.1111/cgf.14059
Leimkühler TSingh GMyszkowski KSeidel HRitschel T(2019)Deep point correlation designACM Transactions on Graphics10.1145/3355089.335656238:6(1-17)Online publication date: 8-Nov-2019
https://dl.acm.org/doi/10.1145/3355089.3356562
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