XU Chen, LI Min, SUN Xiaoli, “An Edge-preserving Variational Method for Image Decomposition,” Chinese Journal of Electronics, vol. 22, no. 1, pp. 109-113, 2013,
Citation: XU Chen, LI Min, SUN Xiaoli, “An Edge-preserving Variational Method for Image Decomposition,” Chinese Journal of Electronics, vol. 22, no. 1, pp. 109-113, 2013,

An Edge-preserving Variational Method for Image Decomposition

Funds:  This work is supported by the National Natural Science Foundation of China (No.61070087), the National Natural Science Funds for Young Scholar (No.61001183) and Guangdong University-industry Cooperation Projects (No.2009B090300355).
  • Received Date: 2011-03-01
  • Rev Recd Date: 2011-06-01
  • Publish Date: 2013-01-05
  • Variational methods for image decomposition have gained considerable attention in recent years. In such approaches, an image usually can be decomposed into a geometrical (or structure) component and a textured (or noise) feature. In this paper we propose an edge-preserving variational model which can split an image into four components: a first one containing the structure of the image, a second one the texture of the image, a third one the noise and a forth one the edge. Our decomposition model relies on the use of three different terms: the edgepreserving regularization for the geometrical component and the edge, a negative Sobolev norm for the texture, and a negative Besov norm for the noise. We explicitly give numerical scheme that is the synthesis of a projection algorithm, a redundant wavelet (or curvelet) soft threshold and two coupled Partial differential equations (PDE’s). Finally we show image decomposition results on synthetic and real image.
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