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

摘要：

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.

关键词： image restoration regularization parameter total variation method

作者: Peng Liu Dingsheng Liu Zhiwen Liu

作者单位: Center for Earth Observation and Digital Earth Chinese Academy of Science, ＃9, Dengzhuang south Road, Beijing, China

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 429-435

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）