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The Power of Box Filters: Real-time Approximation to Large Convolution Kernel by Box-filtered Image Pyramid

Published: 17 November 2019 Publication History

Abstract

This paper presents a novel solution for approximations to some large convolution kernels by leveraging a weighted box-filtered image pyramid set. Convolution filters are widely used, but still compute-intensive for real-time rendering when the kernel size is large. Our algorithm approximates the convolution kernels, such as Gaussian and cosine filters, by two phases of down and up sampling on a GPU. The computational complexity only depends on the input image resolution and is independent of the kernel size. Therefore, our method can be applied to nonuniform blurs, irradiance probe generations, and ray-traced glossy global illuminations in real time, and runs in effective and efficient performance.

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References

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Published In

cover image ACM Conferences
SA '19: SIGGRAPH Asia 2019 Technical Briefs
November 2019
121 pages
ISBN:9781450369459
DOI:10.1145/3355088
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

New York, NY, United States

Publication History

Published: 17 November 2019

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Author Tags

  1. convolution kernel
  2. global illumination
  3. mipmap
  4. ray-tracing
  5. real-time rendering

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  • Research-article
  • Research
  • Refereed limited

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SA '19
Sponsor:
SA '19: SIGGRAPH Asia 2019
November 17 - 20, 2019
QLD, Brisbane, Australia

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Overall Acceptance Rate 178 of 869 submissions, 20%

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