Better Fixed-Point Filtering with Averaging Trees
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Date
2022
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ACM Association for Computing Machinery
Abstract
Production imaging pipelines commonly operate using fixed-point arithmetic, and within these pipelines a core primitive is convolution by small filters - taking convex combinations of fixed-point values in order to resample, interpolate, or denoise. We describe a new way to compute unbiased convex combinations of fixedpoint values using sequences of averaging instructions, which exist on all popular CPU and DSP architectures but are seldom used. For a variety of popular kernels, our averaging trees have higher performance and higher quality than existing standard practice.
Description
CCS Concepts: Computing methodologies -> Image processing Additional Key Words and Phrases: fixed-point arithmetic, image filtering
@inproceedings{10.1145:3543869,
booktitle = {Proceedings of the ACM on Computer Graphics and Interactive Techniques},
editor = {Josef Spjut and Marc Stamminger and Victor Zordan},
title = {{Better Fixed-Point Filtering with Averaging Trees}},
author = {Adams, Andrew and Sharlet, Dillon},
year = {2022},
publisher = {ACM Association for Computing Machinery},
ISSN = {2577-6193},
ISBN = {},
DOI = {10.1145/3543869}
}