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Volume 31 Issue 7
Dec.  2010
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Liu Peng, Liu Ding-sheng, Li Guo-qing. Selecting Regularization Parameter in Time Marching Method Based on the Synchronous Iteration of Noise and Image[J]. Journal of Electronics & Information Technology, 2009, 31(7): 1711-1715. doi: 10.3724/SP.J.1146.2008.00582
Citation: Liu Peng, Liu Ding-sheng, Li Guo-qing. Selecting Regularization Parameter in Time Marching Method Based on the Synchronous Iteration of Noise and Image[J]. Journal of Electronics & Information Technology, 2009, 31(7): 1711-1715. doi: 10.3724/SP.J.1146.2008.00582

Selecting Regularization Parameter in Time Marching Method Based on the Synchronous Iteration of Noise and Image

doi: 10.3724/SP.J.1146.2008.00582
  • Received Date: 2008-05-14
  • Rev Recd Date: 2009-01-15
  • Publish Date: 2009-07-19
  • In order to correctly estimate the variance of noise in iteration, a pure synthesis noise as an image is synchronously iterated with the observation image in de-convolution, and it takes variance of pure noise image as the estimation of the variance of noise in observation image and computes the regularization parameter by the variance. A novel regularization term that can ensure the synchronous changing of the variance of the two noises is proposed in this article. The new regularization term is put into use only in iteration of pure noise image. Under the condition of knowing the variance of noise of image in iteration, this paper established the relationship between the variance of synthetic noise and the regularization parameter, and the relationship was converted to a simple quadratic equation. Experiments confirm that the new algorithm not only better restrains the noise but also avoids the over smoothing. The adaptability of total variation based image restoration is improved.
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