针对立体视频传输中右视点整帧丢失, 提出了一种基于结构相似度(Structural Similarity, SSIM)的立体视频右视点整帧丢失错误隐藏算法。首先, 提出了时域SSIM 和视间SSIM 的概念。然后, 根据视频序列的时域相关性, 将前一时刻右视点图像宏块的预测方式作为丢失图像宏块的预测方式。接着, 将前一时刻右视点图像以宏块为单位进行时域和视间匹配, 求取其以像素为单位的时域SSIM 映射图和视间SSIM 映射图。最后, 计算并比较前一时刻右视点图像每个宏块的时域SSIM 和视间SSIM 值, 得到每个宏块的预测方式, 将其预测方式作为丢失帧中宏块的预测方式, 从而使用运动补偿预测或者视差补偿预测的方法进行恢复。实验结果表明, 与传统的算法和Pang 的算法相比, PSNR 值分别提高了2.76 dB 和3.43 dB, 且本文算法主观效果较好。

An error concealment algorithm in stereoscopic video transmission based on structural similarity (SSIM) is proposed. Firstly, the concepts of temporal and inter-view SSIM are presented. Secondly, according to the temporal correlation of video sequence, the prediction mode of a Macroblock (MB) in the right view on the previous time is taken as the prediction mode of the lost MB. Thirdly, temporal and inter-view correspondence is adopted to obtain the pixel-wise SSIM map of the right view on the previous time. Finally, the prediction of the MB is obtained by comparing the SSIM values of each MB between the temporal and inter-view of the right view in the previous stereo image pairs. Consequently, the given MB prediction mode is taken as the MB mode in the lost frame, and the motion and disparity compensated prediction are used to restore the content of the lost frame. Experimental results show that the proposed algorithm has improved the PSNR by 2.76 dB and 3.43 dB compared with the traditional methods and Pang’s algorithm, respectively. Meanwhile, the proposed algorithm is efficient in improving the subjective quality of the concealed lost frames.