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Conference Papers Year : 2017

Perceptual metric for color transfer methods


In this paper, we propose a perceptual model for evaluating results from color transfer methods. We conduct a user study, which provides a set of subjective scores for triplets of input, target and result images. Then, for each triplet, we compute a number of image features, which objectively characterize a color transfer. To describe the relationship between these features and the subjective scores, we build a regression model with random forests. An analysis and a cross-validation show that the predictions of our model are highly accurate.


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Dates and versions

hal-01651141 , version 1 (28-11-2017)


  • HAL Id : hal-01651141 , version 1


Hristina Hristova, Olivier Le Meur, Rémi Cozot, Kadi Bouatouch. Perceptual metric for color transfer methods. IEEE International Conference on Image Processing - ICIP 2017, Sep 2017, Shanghai, China. ⟨hal-01651141⟩
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