Predicting range of acceptable photographic tonal adjustments
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
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There is often more than one way to select tonal adjustment for a photograph, and different individuals may prefer different adjustments. However, selecting good adjustments is challenging. This thesis describes a method to predict whether a given tonal rendition is acceptable for a photograph, which we use to characterize its range of acceptable adjustments. We gathered a dataset of image "acceptability" over brightness and contrast adjustments. We find that unacceptable renditions can be explained in terms of over-exposure, under-exposure, and low contrast. Based on this observation, we propose a machine-learning algorithm to assess whether an adjusted photograph looks acceptable. We show that our algorithm can differentiate unsightly renditions from reasonable ones. Finally, we describe proof-of-concept applications that use our algorithm to guide the exploration of the possible tonal renditions of a photograph.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.Cataloged from PDF version of thesis.Includes bibliographical references (pages 57-58).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.