中文摘要：

提出了一种新的基于联合字典学习的图像去噪方法。考虑图像复原问题总是涉及高、低质量两个版本的图像，从大量图像的两个版本中成对采样联合训练字典。所得字典不仅具有某类样本图像的结构特征，更具有一般图像这两个版本之间的对应关系，因此使得图像复原估计更有指向性，复原结果与原图像在细节上也更接近。

英文摘要：

A novel approach of denoising is presented based on joint-dictionary learning .It is considered that there are always two versions of images with high and low quality in image restoration problems .The samples are taken from a pair of these images once a time for joint-dictionary training .As a result , a dictionary containing not only the samples＇structure features but also the relationship between images of these two versions is obtained .So when a degraded image is to be recovered , the joint-learned dictionary will work as an assistance to help to get a more precise estimation to the original image .