Department of Mathematics
 Search | Help | Login | pdf version | printable version

Math @ Duke



Publications [#264945] of Guillermo Sapiro

Papers Published

  1. Tang, B; Sapiro, G; Caselles, V, Color image enhancement via chromaticity diffusion., IEEE Transactions on Image Processing, vol. 10 no. 5 (2001), pp. 701-707, ISSN 1057-7149 [18249660], [doi]
    (last updated on 2017/12/18)

    A novel approach for color image denoising is proposed in this paper. The algorithm is based on separating the color data into chromaticity and brightness, and then processing each one of these components with partial differential equations or diffusion flows. In the proposed algorithm, each color pixel is considered as an n-dimensional vector. The vectors' direction, a unit vector, gives the chromaticity, while the magnitude represents the pixel brightness. The chromaticity is processed with a system of coupled diffusion equations adapted from the theory of harmonic maps in liquid crystals. This theory deals with the regularization of vectorial data, while satisfying the intrinsic unit norm constraint of directional data such as chromaticity. Both isotropic and anisotropic diffusion flows are presented for this n-dimensional chromaticity diffusion flow. The brightness is processed by a scalar median filter or any of the popular and well established anisotropic diffusion flows for scalar image enhancement. We present the underlying theory, a number of examples, and briefly compare with the current literature.
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320