基于边缘先验模型的运动去模糊

从单幅运动模糊图像复原出清晰的图像,一直是数字图像处理领域中富有挑战的问题.基于边缘先验模型和小波分析提出了一种运动模糊退化图像的复原算法.在去模糊之前,对图像进行预处理,将噪声去除,用冲击滤波器增强边缘,并采用canny边缘检测获取清晰边缘作为先验模型,以此估计模糊核;然后在紧小波框架系统下,将清晰图像的稀疏性最大化,采用改进的分裂Bregman方法求解最优化问题,最终得到清晰的图像.实验结果表明,相对于传统的盲复原算法,提出的方法可以有效地去除运动模糊.

Motion Deblurring Based on Edge Prior Model

How to restore clear images from degraded images is a challenging problem in the field of digital image processing.This paper proposed a restoration algorithm for motion blurred image based on edge prior model and wavelet analysis.We applied a preprocessing procedure before deblurring to remove noise,and then used shock filter to enhance edges and canny edge detection to get clear edges for estimating kernel.After that,we maximized the sparsity of clear image under tight wavelet frame system.Furthermore,the adapted split Bregman method was proposed to solve the optimization problem.Finally,the clear image can be got.The experimental results show that compared with traditional blind restoration algorithms,the proposed method can effectively remove the motion blur.