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Volume 31 Issue 1
Dec.  2010
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Lu Cheng-wu, Song Guo-xiang. An Image Denoising Method Using Total Variation Regularization for Flow Field[J]. Journal of Electronics & Information Technology, 2009, 31(1): 112-115. doi: 10.3724/SP.J.1146.2007.01039
Citation: Lu Cheng-wu, Song Guo-xiang. An Image Denoising Method Using Total Variation Regularization for Flow Field[J]. Journal of Electronics & Information Technology, 2009, 31(1): 112-115. doi: 10.3724/SP.J.1146.2007.01039

An Image Denoising Method Using Total Variation Regularization for Flow Field

doi: 10.3724/SP.J.1146.2007.01039
  • Received Date: 2007-06-25
  • Rev Recd Date: 2007-11-30
  • Publish Date: 2009-01-19
  • Using image decomposition theory proposed by Meyer, a total variation image denoising method based on smoothing flow field is presented. Firstly, through applying Hilbert-Sobolev norm to measure fidelity term, a total variation filter is used to smooth the normal vectors of the level curves of a noise image. And then, a model is constructed to find a surface which fit smoothed normal vectors. Finally, finite difference schemes are used to solve the Euler-Lagrange functions derived from above models. The experiments show that the approach not only can remove noisy efficiently, but also can retain edges and texture.
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