A Framework for Interactive Image Color Editing

Przemyslaw Musialski, Ming Cui, Jieping Ye, Anshuman Razdan, Peter Wonka
A Framework for Interactive Image Color Editing
The Visual Computer, (), 2012. [ draft]
Content:

Information

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.

Additional Files and Images

Additional images and videos:
comparison comparison: comparison to other methods
results results: results of the proposed method
Additional files:
draft draft: paper draft [8MB]

BibTeX

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@article{musialski_2012_fice,
  title =      "A Framework for Interactive Image Color Editing",
  author =     "Przemyslaw Musialski and Ming Cui and Jieping Ye and
               Anshuman Razdan and Peter Wonka",
  year =       "2012",
  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.",
  pages =      "%pages_from%--%pages_to%",
  journal =    "The Visual Computer",
  keywords =   "computational photography, recoloring, image processing,
               color manipulation, interactive image editing",
  URL =        "http://www.cg.tuwien.ac.at/research/publications/2012/musialski_2012_fice/",
}