本文针对 3D图像压缩过程产生的块效应，提出了一种基于联合字典的 3D图像去块效应方法。该方法主要包括字典训练、字典联合和去块效应三个阶段。在字典训练阶段，采用字典学习方法分别训练得到过完备的彩色字典和深度字典；在字典联合阶段，根据测试图像的稀疏特性和构造的彩色和深度字典，求出对应的彩色与深度联合字典；在去块效应阶段，通过估计重构误差阈值，并根据联合字典对图像进行去块效应处理。实验结果表明，本文提出的方法能够有效地去除编码图像的块效应，且得到较高的虚拟视点绘制质量。

To eliminate the blocking artifacts caused by three-dimensional (3D) image compression, a deblocking method is proposed based on joint dictionary. The proposed method mainly includes three stages: dictionary training, dictionary jointing and deblocking. At the dictionary training stage, an over-complete color dictionary and depth dictionary are trained respectively with state-of-the-art dictionary learning method. At the dictionary jointing stage, for a testing sample, its corresponding color-depth joint dictionary is constructed based on the sparse coefficients with respect to the learnt color and depth dictionaries. At the deblocking stage, by estimating the reconstruction error threshold, a deblocking operation is performed to get the reconstructed 3D images with respect to the learnt joint dictionary. Experimental results demonstrate that the proposed method can effectively reduce the blocking artifacts of the compressed 3D images and generate high-quality synthesized images.