A model of local adaptation
A model of local adaptation
The visual system constantly adapts to different luminance levels when viewing natural scenes. The state of visual adaptation is the key parameter in many visual models. While the time-course of such adaptation is well understood, there is little known about the spatial pooling that drives the adaptation signal. In this work we propose a new empirical model of local adaptation, that predicts how the adaptation signal is integrated in the retina. The model is based on psychophysical measurements on a high dynamic range (HDR) display. We employ a novel approach to model discovery, in which the experimental stimuli are optimized to find the most predictive model. The model can be used to predict the steady state of adaptation, but also conservative estimates of the visibility (detection) thresholds in complex images. We demonstrate the utility of the model in several applications, such as perceptual error bounds for physically based rendering, determining the backlight resolution for HDR displays, measuring the maximum visible dynamic range in natural scenes, simulation of afterimages, and gaze-dependent tone mapping.
Vangorp, Peter
0e8ca217-1d40-47bd-8384-570a4b89aad5
Myszkowski, Karol
c297140c-2bc4-4844-8ecc-5113ea9eaf48
Graf, Erich W.
1a5123e2-8f05-4084-a6e6-837dcfc66209
Mantiuk, Rafal K.
1dba70cb-ab2c-46aa-9930-336a0115e255
November 2015
Vangorp, Peter
0e8ca217-1d40-47bd-8384-570a4b89aad5
Myszkowski, Karol
c297140c-2bc4-4844-8ecc-5113ea9eaf48
Graf, Erich W.
1a5123e2-8f05-4084-a6e6-837dcfc66209
Mantiuk, Rafal K.
1dba70cb-ab2c-46aa-9930-336a0115e255
Vangorp, Peter, Myszkowski, Karol, Graf, Erich W. and Mantiuk, Rafal K.
(2015)
A model of local adaptation.
ACM Transactions on Graphics, 34 (6), [166].
(doi:10.1145/2816795.2818086).
Abstract
The visual system constantly adapts to different luminance levels when viewing natural scenes. The state of visual adaptation is the key parameter in many visual models. While the time-course of such adaptation is well understood, there is little known about the spatial pooling that drives the adaptation signal. In this work we propose a new empirical model of local adaptation, that predicts how the adaptation signal is integrated in the retina. The model is based on psychophysical measurements on a high dynamic range (HDR) display. We employ a novel approach to model discovery, in which the experimental stimuli are optimized to find the most predictive model. The model can be used to predict the steady state of adaptation, but also conservative estimates of the visibility (detection) thresholds in complex images. We demonstrate the utility of the model in several applications, such as perceptual error bounds for physically based rendering, determining the backlight resolution for HDR displays, measuring the maximum visible dynamic range in natural scenes, simulation of afterimages, and gaze-dependent tone mapping.
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e-pub ahead of print date: 4 November 2015
Published date: November 2015
Additional Information:
Proceedings of ACM SIGGRAPH Asia 2015
Organisations:
Cognition
Identifiers
Local EPrints ID: 381947
URI: http://eprints.soton.ac.uk/id/eprint/381947
ISSN: 0730-0301
PURE UUID: 8ae004d1-b6fa-43a8-b941-d6bd4096b9a2
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Date deposited: 19 Oct 2015 10:31
Last modified: 15 Mar 2024 03:19
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Contributors
Author:
Peter Vangorp
Author:
Karol Myszkowski
Author:
Rafal K. Mantiuk
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