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Colorization Using Segmentation with Random Walk

  • Xiaoming Liu
  • Jun Liu
  • Zhilin Feng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5702)

Abstract

Traditional monochrome image colorization techniques require considerable user interaction and a lot of time. The segment-based colorization works fast but at the expense of detail loss because of the large segmentation; while the optimization based method looks much more continuous but takes longer time. This paper proposed a novel approach: Segmentation colorization based on random walks, which is a fast segmentation technique and can naturally handle multi-label segmentation problems. It can maintain smoothness almost everywhere except for the sharp discontinuity at the boundaries in the images. Firstly, with the few seeds of pixels set manually scribbled by the user, a global energy is set up according to the spatial information and statistical grayscale information. Then, with random walks, the global optimal segmentation is obtained fast and efficiently. Finally, a banded graph cut based refine procedure is applied to deal with ambiguous regions of the previous segmentation. Several results are shown to demonstrate the effectiveness of the proposed method.

Keywords

colorization random walks graph cut image segmentation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Xiaoming Liu
    • 1
  • Jun Liu
    • 1
  • Zhilin Feng
    • 2
  1. 1.College of Computer Science and TechnologyWuhan University of Science and TechnologyWuhanChina
  2. 2.Zhijiang CollegeZhejiang University of TechnologyHangzhouChina

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