改进的空间自适应规整化图像复原

Improved spatially adaptive regularized image restoration

在对空间自适应规整化图像复原算法的研究中发现,如果图像中混杂有椒盐噪声,则自适应算法的复原效果并不理想。针对这一问题,提出了一种新的可见度函数,用模糊熵代替均方差作为评价图像灰度值变化程度的判据,使得算法在提高复原图像质量的同时,能够适应更多类型噪声的干扰。仿真实验结果表明,在椒盐噪声存在的情况下,新算法的性能远优于原算法,对模糊-噪声图像的复原结果也在实验中给出。

In the research on spatially adaptive regularized image restoration algorithm, it is observed that the effect of the algorithm is not satisfactory in the case that there is salt and pepper noise in the image.In order to solve this problem,a new visibility function is presented,in which fuzzy entropy is substitute to mean square error to evaluate the spatial aetivity of the image,so the algorithm can accommodate the disturb of more kinds of noise,with the quality improvement of restorations.Computer simulation shows that the performance of the new algorithm is much better than the traditional one in the presence of salt and pepper noise and the restored result of blurred-noisy image is given in the experiment.