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FLIP: A Difference Evaluator for Alternating Images

Andersson, Pontus LU orcid ; Akenine-Möller, Tomas LU ; Nilsson, Jim ; Åström, Kalle LU orcid ; Oskarsson, Magnus LU orcid and Fairchild, Mark (2020) In Proceedings of the ACM in Computer Graphics and Interactive Techniques 3(2). p.1-23
Abstract
Image quality measures are becoming increasingly important in the field of computer graphics. For example, there is currently a major focus on generating photorealistic images in real time by combining path tracing with denoising, for which such quality assessment is integral. We present FLIP, which is a difference evaluator with a particular focus on the differences between rendered images and corresponding ground truths. Our algorithm produces a map that approximates the difference perceived by humans when alternating between two images. FLIP is a combination of modified existing building blocks, and the net result is surprisingly powerful. We have compared our work against a wide range of existing image difference algorithms and we have... (More)
Image quality measures are becoming increasingly important in the field of computer graphics. For example, there is currently a major focus on generating photorealistic images in real time by combining path tracing with denoising, for which such quality assessment is integral. We present FLIP, which is a difference evaluator with a particular focus on the differences between rendered images and corresponding ground truths. Our algorithm produces a map that approximates the difference perceived by humans when alternating between two images. FLIP is a combination of modified existing building blocks, and the net result is surprisingly powerful. We have compared our work against a wide range of existing image difference algorithms and we have visually inspected over a thousand image pairs that were either retrieved from image databases or generated in-house. We also present results of a user study which indicate that our method performs substantially better, on average, than the other algorithms. To facilitate the use of FLIP, we provide source code in C++, MATLAB, NumPy/SciPy, and PyTorch. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Proceedings of the ACM in Computer Graphics and Interactive Techniques
volume
3
issue
2
article number
15
pages
23 pages
publisher
Association for Computing Machinery (ACM)
external identifiers
  • scopus:85105482622
ISSN
2577-6193
DOI
10.1145/3406183
project
Evaluating and Improving Rendered Visual Experiences
WASP: Wallenberg AI, Autonomous Systems and Software Program at Lund University
language
English
LU publication?
yes
id
397ced35-879a-43a6-a225-ce31b0e984a2
alternative location
https://research.nvidia.com/sites/default/files/node/3260/FLIP_Paper.pdf
date added to LUP
2020-08-31 11:48:42
date last changed
2024-03-05 03:30:31
@article{397ced35-879a-43a6-a225-ce31b0e984a2,
  abstract     = {{Image quality measures are becoming increasingly important in the field of computer graphics. For example, there is currently a major focus on generating photorealistic images in real time by combining path tracing with denoising, for which such quality assessment is integral. We present FLIP, which is a difference evaluator with a particular focus on the differences between rendered images and corresponding ground truths. Our algorithm produces a map that approximates the difference perceived by humans when alternating between two images. FLIP is a combination of modified existing building blocks, and the net result is surprisingly powerful. We have compared our work against a wide range of existing image difference algorithms and we have visually inspected over a thousand image pairs that were either retrieved from image databases or generated in-house. We also present results of a user study which indicate that our method performs substantially better, on average, than the other algorithms. To facilitate the use of FLIP, we provide source code in C++, MATLAB, NumPy/SciPy, and PyTorch.}},
  author       = {{Andersson, Pontus and Akenine-Möller, Tomas and Nilsson, Jim and Åström, Kalle and Oskarsson, Magnus and Fairchild, Mark}},
  issn         = {{2577-6193}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{1--23}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  series       = {{Proceedings of the ACM in Computer Graphics and Interactive Techniques}},
  title        = {{FLIP: A Difference Evaluator for Alternating Images}},
  url          = {{http://dx.doi.org/10.1145/3406183}},
  doi          = {{10.1145/3406183}},
  volume       = {{3}},
  year         = {{2020}},
}