Journal article 1264 views 89 downloads
Analysis of reported error in Monte Carlo rendered images
The Visual Computer, Volume: 33, Issue: 6-8, Pages: 705 - 713
Swansea University Author:
Mark Jones
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DOI (Published version): 10.1007/s00371-017-1384-7
Abstract
Evaluating image quality in Monte Carlo rendered images is an important aspect of the rendering process as we often need to determine the relative quality between images computed using different algorithms and with varying amounts of computation. The use of a gold-standard, reference image, or groun...
Published in: | The Visual Computer |
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ISSN: | 0178-2789 1432-2315 |
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Springer Science and Business Media LLC
2017
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URI: | https://cronfa.swan.ac.uk/Record/cronfa33015 |
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2020-07-30T08:56:48.4505913 v2 33015 2017-04-22 Analysis of reported error in Monte Carlo rendered images 2e1030b6e14fc9debd5d5ae7cc335562 0000-0001-8991-1190 Mark Jones Mark Jones true false 2017-04-22 SCS Evaluating image quality in Monte Carlo rendered images is an important aspect of the rendering process as we often need to determine the relative quality between images computed using different algorithms and with varying amounts of computation. The use of a gold-standard, reference image, or ground truth (GT) is a common method to provide a baseline with which to compare experimental results. We show that if not chosen carefully the reference image can skew results leading to significant misreporting of error. We present an analysis of error in Monte Carlo rendered images and discuss practices to avoid or be aware of when designing an experiment. Journal Article The Visual Computer 33 6-8 705 713 Springer Science and Business Media LLC 0178-2789 1432-2315 Image quality assessment; Error metric; Monte Carlo rendering 1 6 2017 2017-06-01 10.1007/s00371-017-1384-7 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University RCUK 2020-07-30T08:56:48.4505913 2017-04-22T13:52:41.0880562 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Joss Whittle 1 Mark Jones 0000-0001-8991-1190 2 Rafał Mantiuk 3 33015__17807__aa1be2ecadb745b98021fe2efab713e8.pdf 2017_MC_Errorv2.pdf 2020-07-30T08:54:51.5050046 Output 2447814 application/pdf Version of Record true Released under the terms of a Creative Commons Attribution License (CC-BY). true eng http://creativecommons.org/licenses/by/4.0/ |
title |
Analysis of reported error in Monte Carlo rendered images |
spellingShingle |
Analysis of reported error in Monte Carlo rendered images Mark Jones |
title_short |
Analysis of reported error in Monte Carlo rendered images |
title_full |
Analysis of reported error in Monte Carlo rendered images |
title_fullStr |
Analysis of reported error in Monte Carlo rendered images |
title_full_unstemmed |
Analysis of reported error in Monte Carlo rendered images |
title_sort |
Analysis of reported error in Monte Carlo rendered images |
author_id_str_mv |
2e1030b6e14fc9debd5d5ae7cc335562 |
author_id_fullname_str_mv |
2e1030b6e14fc9debd5d5ae7cc335562_***_Mark Jones |
author |
Mark Jones |
author2 |
Joss Whittle Mark Jones Rafał Mantiuk |
format |
Journal article |
container_title |
The Visual Computer |
container_volume |
33 |
container_issue |
6-8 |
container_start_page |
705 |
publishDate |
2017 |
institution |
Swansea University |
issn |
0178-2789 1432-2315 |
doi_str_mv |
10.1007/s00371-017-1384-7 |
publisher |
Springer Science and Business Media LLC |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science |
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description |
Evaluating image quality in Monte Carlo rendered images is an important aspect of the rendering process as we often need to determine the relative quality between images computed using different algorithms and with varying amounts of computation. The use of a gold-standard, reference image, or ground truth (GT) is a common method to provide a baseline with which to compare experimental results. We show that if not chosen carefully the reference image can skew results leading to significant misreporting of error. We present an analysis of error in Monte Carlo rendered images and discuss practices to avoid or be aware of when designing an experiment. |
published_date |
2017-06-01T03:40:38Z |
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1763751848323317760 |
score |
11.021648 |