Francesco Banterle
Mixing tone mapping operators on the GPU by differential zone mapping based on psychophysical experiments
Banterle, Francesco; Artusi, Alessandro; Sikudova, Elena; Ledda, Patrick; Bashford-Rogers, Thomas; Chalmers, Alan; Bloj, Marina
Authors
Alessandro Artusi
Elena Sikudova
Patrick Ledda
Tom Bashford-Rogers Tom.Bashford-Rogers@uwe.ac.uk
Associate Lecturer - CATE - CSCT - UCSC0000
Alan Chalmers
Marina Bloj
Abstract
© 2016 In this paper, we present a new technique for displaying High Dynamic Range (HDR) images on Low Dynamic Range (LDR) displays in an efficient way on the GPU. The described process has three stages. First, the input image is segmented into luminance zones. Second, the tone mapping operator (TMO) that performs better in each zone is automatically selected. Finally, the resulting tone mapping (TM) outputs for each zone are merged, generating the final LDR output image. To establish the TMO that performs better in each luminance zone we conducted a preliminary psychophysical experiment using a set of HDR images and six different TMOs. We validated our composite technique on several (new) HDR images and conducted a further psychophysical experiment, using an HDR display as the reference that establishes the advantages of our hybrid three-stage approach over a traditional individual TMO. Finally, we present a GPU version, which is perceptually equal to the standard version but with much improved computational performance.
Citation
Banterle, F., Artusi, A., Sikudova, E., Ledda, P., Bashford-Rogers, T., Chalmers, A., & Bloj, M. (2016). Mixing tone mapping operators on the GPU by differential zone mapping based on psychophysical experiments. Signal Processing: Image Communication, 48, 50-62. https://doi.org/10.1016/j.image.2016.09.004
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 1, 2016 |
Online Publication Date | Sep 12, 2016 |
Publication Date | Oct 1, 2016 |
Deposit Date | Oct 23, 2017 |
Publicly Available Date | Oct 23, 2017 |
Journal | Signal Processing: Image Communication |
Print ISSN | 0923-5965 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 48 |
Pages | 50-62 |
DOI | https://doi.org/10.1016/j.image.2016.09.004 |
Keywords | high dynamic range imaging, tone mapping operators, real-time tone mapping, GPU programming |
Public URL | https://uwe-repository.worktribe.com/output/907387 |
Publisher URL | https://doi.org/10.1016/j.image.2016.09.004 |
Files
DZMGPU.pdf
(39.3 Mb)
PDF
You might also like
A wide spectral range sky radiance model
(2022)
Journal Article
Deep learning-based defect inspection in sheet metal stamping parts
(2022)
Conference Proceeding
Deep synthesis of cloud lighting
(2022)
Journal Article
Ensemble metropolis light transport
(2021)
Journal Article
Deception in network defences using unpredictability
(2021)
Journal Article