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A framework for interactive image color editing

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Abstract

We propose a new method for interactive image color replacement that creates smooth and naturally looking results with minimal user interaction. Our system expects as input a source image and rawly scribbled target color values and generates high quality results in interactive rates. To achieve this goal we introduce an algorithm that preserves pairwise distances of the signatures in the original image and simultaneously maps the color to the user defined target values. We propose efficient sub-sampling in order to reduce the computational load and adapt semi-supervised locally linear embedding to optimize the constraints in one objective function. We show the application of the algorithm on typical photographs and compare the results to other color replacement methods.

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Notes

  1. Note that there is another high-level relationship between diffusion distance and locally linear embedding since both methods are based on spectral graph analysis. However, this issue does not affect our algorithm and is beyond the scope of this paper (cf. Nadler et al. [19]).

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Acknowledgements

This research was financially supported by Science Foundation Arizona, US Navy, and NSF. We would like tom thank Tom Ang (Fig. 14) and Norman Koren (Figs. 1, 5) for the permission to use their outstanding photographs.

Fig. 14
figure 14

Result of our recoloring method. In each row, from left to right: original, user input in form of strokes, our output. All original images in this figure are copyrighted by Tom Ang (http://www.tomang.com/). Best seen in the electronic version in close-up

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Fig. 15
figure 15

Our method can also be used to custom black-white conversion and it also allows selective conversion of spatial regions. Best seen in the electronic version in close-up

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Authors and Affiliations

  1. Vienna University of Technology, Vienna, Austria

    Przemyslaw Musialski

  2. Arizona State University, Tempe, AZ, USA

    Przemyslaw Musialski, Ming Cui, Jieping Ye, Anshuman Razdan & Peter Wonka

  3. King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

    Peter Wonka

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  1. Przemyslaw Musialski
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  2. Ming Cui
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Correspondence to Przemyslaw Musialski.

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Musialski, P., Cui, M., Ye, J. et al. A framework for interactive image color editing. Vis Comput 29, 1173–1186 (2013). https://doi.org/10.1007/s00371-012-0761-5

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