Selecting Regularization Parameter in Time Marching Method Based on the Synchronous Iteration of Noise and Image
Liu Peng①②; Liu Ding-sheng①; Li Guo-qing①
①Center for Earth Observation and Digital Earth Chinese Academy of Science, Beijing 100086, China; ②Institute of Electronics Chinese Academy of Sciences, Beijing 100190, China
Abstract：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.
刘 鹏; 刘定生; 李国庆. 基于噪声与图像同步迭代来确定时间步进法的规整化参数[J]. 电子与信息学报, 2009, 31(7): 1711-1715 .
Liu Peng①②; Liu Ding-sheng①; Li Guo-qing①. Selecting Regularization Parameter in Time Marching Method Based on the Synchronous Iteration of Noise and Image. , 2009, 31(7): 1711-1715 .
2009, Vol. 31 
