A model of visual adaptation for realistic image synthesis
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
A multiscale model of adaptation and spatial vision for realistic image display
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Gradient domain high dynamic range compression
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Fast bilateral filtering for the display of high-dynamic-range images
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Photographic tone reproduction for digital images
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
A Visibility Matching Tone Reproduction Operator for High Dynamic Range Scenes
IEEE Transactions on Visualization and Computer Graphics
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ACM '68 Proceedings of the 1968 23rd ACM national conference
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ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Fast Tone Mapping for High Dynamic Range Images
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CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Two-scale tone management for photographic look
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Interactive local adjustment of tonal values
ACM SIGGRAPH 2006 Papers
ImprovingWeb-based Image Search via Content Based Clustering
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
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CGIM '08 Proceedings of the Tenth IASTED International Conference on Computer Graphics and Imaging
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ACM SIGGRAPH 2011 papers
Data-driven visual similarity for cross-domain image matching
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Learning photographic global tonal adjustment with a database of input/output image pairs
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Automatic exposure correction of consumer photographs
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
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In this paper we propose a different approach to high dynamic range (HDR) image tone mapping. We put away the assumption that there is a single optimal solution to tone mapping. We argue that tone mapping is inherently a personal process that is guided by the taste and preferences of the artist; different artists can produce different depictions of the same scene. However, most existing tone mapping operators (TMOs) compel the artists to produce similar renderings. Operators that give more freedom to artists require adjustment of many parameters which turns tone mapping into a laborious process. In contrast to these, we propose an algorithm which learns the taste and preferences of an artist from a small set of calibration images. Any new image is then tone mapped to convey the appearance that would be desired by the artist.