基于模糊函数估计和变分泛函数优化的含噪声模糊图像复原算法

Spread Point Function Estimation and Variational Function Based Image Restoration Algorithm for Blurring and Noisy Image

针对摄影图像中常见的噪声和模糊同时退化图像的问题,提出一种Radon变换估计模糊函数结合变分泛函优化的图像复原算法.算法首先利用方向滤波器对图像去噪,然后利用Radon变换以去除方向滤波在模糊函数估计中引起的偏差,再利用模糊函数通过去卷积操作去除模糊,最后在去模糊的基础上利用L0梯度范数的变换泛函的优化算法,去除剩余噪声从而对图像进行复原.实验表明,该算法可以有效地恢复摄影图像中的场景.

An image restoration based on Radon transform and minimizing variational function was proposed, inorder to restore the blurring and noisy images by photography. The proposed algorithm firstly de-noised the blurring and noisy image by directional filter, then estimated the spread point function based on Radon transform which can eliminate error of the estimation due to the directional filter. Since then, the original image was de-burred by de-convolution with the spread point function. Finally, the de-blurred image was further de-noised by the variational function with L0-norm regularization. By experiments, the proposed algorithm can restore blurring and noisy images.