摘要
真实环境中得到的图像常会受到多种模糊降质过程的影响,导致成像质量下降,为此提出一种图像退化模型及相应的复原算法.与传统的级联方式不同,该算法假定模糊核函数是散焦与运动模糊的加权和形式;在散焦模糊给定的情况下,使用广义拉普拉斯分布作为运动模糊的统计模型,并在期望最大化(EM)算法框架下估计模糊核函数;最后利用估计的模糊核函数进行图像复原.实验结果表明,采用文中的复原算法能够较为准确地辨识出模糊核,提升了图像复原的效果.
Due to image restoration the comp method licacy of environment, digital images may be degraded by for the degradation model is proposed in this paper. approaches, we assume that the blur kernel is the mixture of defocus and motion various blurs. An Unlike traditional blurs. Given the defocus blur, the statistical characteristic of the motion blur is exploited by using generalized Laplacian model, and then the mixed blur is identified using the expectation maximization （EM） algorithm. Finally the degraded image can be restored based on the estimated blur. Experimental results demonstrate that the proposed method could identify the blur effectively, and improve visual quality of the degraded images.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2010年第2期272-278,共7页
Journal of Computer-Aided Design & Computer Graphics
基金
国家科技支撑计划重点项目(2006BAK07B04)
