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Tone Mapping by Interactive Evolution
Tone mapping is a computational task of significance in the context of
displaying high dynamic range images on low dynamic range devices. While a
number of tone mapping algorithms have been proposed and are in common use,
there is no single operator that yields optimal results under all
conditions. Moreover, obtaining satisfactory mappings often requires the
manual tweaking of parameters the influence of which is not always easily
understood.
While the quality of a tone mapped image is difficult to assess
algorithmically, human subjects typically have no trouble distinguishing
well tone mapped images from poorly mapped ones. We thus propose interactive
evolutionary algorithms as a tool for tone mapping. Tone mapped images are
generated by blending the results obtained from a number of commonly used
tone mapping operators in a perceptually uniform colour space. The weights
that determine the relative influence of the individual operators together
with the operators' parameters form a vector of real-valued variables. An
evolution strategy with subjective selection is used to iteratively improve
the appearance of the tone mapped images. Importantly, adjustments to the
mapping are made in the interactive evolutionary process without a need for
the user to understand the influence of the operators' parameters. A user of
the system simply needs to pick the most appealing out of a set of
automatically generated images. The motivation for blending the images
obtained from several tone mapping operators is that mappings that cannot be
generated by any one of the individual operators may be achieved. Rather
than having to pick the operator most appropriate for the image at hand (and
having to accept its limitations), a good mapping that may be outside of the
range of any one operator can be found.
Publications
S. B. Chisholm, D. V. Arnold, and S. Brooks
Tone mapping by
interactive evolution
Genetic and Evolutionary Computation Conference, Montreal, 2009.
S. B. Chisholm
Tone Mapping by Interactive Evolution
Masters thesis, Dalhousie University, 2009.
Support
This research is supported through grants from the Natural Sciences and
Engineering Research Council of Canada (NSERC) and the Canada Foundation
for Innovation (CFI).
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