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Propagating sparse labels through edge-aware filters

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Abstract

In this paper, we show how linear, but not necessarily shift-invariant, filters can be used to propagate sparse labels throughout an image. We propose a new propagation method based on the domain transform filter, a linear, shift-varying filter whose kernel width varies based on local edge information. We contrast this against the more well-known energy minimization approach and show that it can produce significantly better results when the input labels contain errors. Finally, we show how minimization-based methods are better suited for purely user-guided applications.

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Notes

  1. A filter is linear if \(h\{Ax[n] + By[n]\} = Ah\{x[n]\} + Bh\{y[n]\}.\)

  2. \(\sigma _s\) has minimal effect provided it is relatively large. See [15] for more information on the parameters.

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Authors and Affiliations

  1. Bubl Technology Inc., 324–171 East Liberty St., Toronto, ON, M6K 3P6, Canada

    Richard Rzeszutek

  2. Department of Electrical and Computer Engineering, Ryerson University, 350 Victoria St., Toronto, ON, M5B 2K3, Canada

    Dimitrios Androutsos

Authors
  1. Richard Rzeszutek
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  2. Dimitrios Androutsos
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Correspondence to Richard Rzeszutek.

Additional information

This work was done while R. Rzeszutek was a Ph.D. candidate at Ryerson University.

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Rzeszutek, R., Androutsos, D. Propagating sparse labels through edge-aware filters. SIViP 9 (Suppl 1), 17–24 (2015). https://doi.org/10.1007/s11760-015-0833-x

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