Selection of Regularization Parameter Based on Synchronous Noise in Total Variation Image Restoration

In this article, we apply the total variation method to image restoration. We propose a method to calculate the regularization parameter in which we establish the relationship between the noise and the regularization parameter. To correctly estimate the variance of the noise remaining in image, we synchronously iterate a synthesized noise with the observed image in deconvolution. We take the variance of the synthesized noise to be the estimate of the variance of the noise remaining in the estimated image, and we propose a new regularization term that ensures that the synthetic noise and the real noise change in a synchronous manner. The similarity in the statistical properties of the real noise and the synthetic noise can be maintained in iteration. We then establish the relationship between the variance of synthetic noise and the regularization parameter. In every iteration, the regularization parameter is calculated by using the formula proposed for the relationship. The experiments confirm that, by using this method, the performance of the total variation image restoration is improved.