Texture segmentation using directional empirical mode decomposition

@article{Liu2004TextureSU,
  title={Texture segmentation using directional empirical mode decomposition},
  author={Zhongxuan Liu and Hongjian Wang and Silong Peng},
  journal={2004 International Conference on Image Processing, 2004. ICIP '04.},
  year={2004},
  volume={1},
  pages={279-282 Vol. 1}
}
In this paper the technique of directional empirical mode decomposition (DEMD) and its application to texture segmentation are presented. Empirical mode decomposition (EMD) decomposes signals by sifting and then analyzes the instantaneous frequency of the obtained components called intrinsic mode functions (IMF). As a new form of extending 1D EMD to the 2D case, DEMD considers the directional frequency and envelope at each point. One type of 2D Hilbert transform is introduced to compute the… CONTINUE READING
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