In order to effectively protect video information, according to the characteristics of H.265/HEVC (High Efficiency Video Coding), a scheme combining transform coefficient scrambling and syntax element encryption was proposed. For Transform Unit (TU), the TU with the size of 4×4 was scrambled by Arnold transform. At the same time, a shift cipher was designed, and the cipher was initialized according to the approximate distribution rule of the Direct Current (DC) coefficient of the TU, and the DC coefficients of TU with the size of 8×8, 16×16 and 32×32 were shifting encrypted using encryption map generated by Arnold transform. For some of the syntax elements with bypass coding used in the entropy coding process, the Logistic chaotic sequence was used for encryption. After encryption, the Peak Signal-to-Noise Ratio (PSNR) and Structual Similarity (SSIM) of the video were decreased by 26.1 dB and 0.51 respectively on average, while the compression ratio was only decreased by 1.126% and the coding time was only increased by 0.17%. Experimental results show that under the premise of ensuring better encryption effect and less impact on bit rate, the proposed scheme has less extra coding overhead and is suitable for real-time video applications.

Focusing on the issue that most of the existing evaluation methods transform images into different coordinate domain, a spatial Natural Scene Statistics (NSS) based model of no reference stereoscopic image quality assessment method was proposed. Among the stereoscopic image quality assessment, in order to better combine with the binocular visual features of human beings, left and right images were fused to construct a cyclopean map. Firstly, via statistical distribution of the Cyclopean Mean Subtracted Contrast Normalized (CMSCN) coefficients, the natural scene statistical characteristics were extracted in spatial domain from the cyclopean map. Secondly, by getting statistical distribution of the Disparity Mean Subtracted Contrast Normalized (DMSCN) coefficients, and the same characteristics were extracted from the disparity map obtained by optical flow model. Finally, Support Vector Regression (SVR) was performed to predict the objective scores of stereoscopic images by establishing the relationship between the stereoscopic image feature information and the Difference Mean Opinion Score (DMOS). The experimental results show that compared with other methods, the Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank-Order Correlation Coefficient (SROCC) indicators reach 0.94 on symmetric stereoscopic image database, and the PLCC indicator reaches 0.91 and the SROCC indicator reaches 0.93 on asymmetric stereoscopic image database, which indicate the proposed method can achieve higher consistency with subjective assessment of stereoscopic images.

The existing error concealment algorithms for I frame are difficult to balance the recovery image quality and the algorithm complexity. To solve the problem, an efficient intra-fame partitioning error concealment method was proposed. Firstly, according to the motion correlation between video frames, the lost macro blocks were divided into motion blocks and static blocks. For static blocks, frame copy error concealment method was used to conceal lost blocks. For motion blocks, they were divided into smooth blocks and texture blocks by the texture information of the correctly decoded macro blocks. Then, the bilinear interpolation method was adopted to restore the smooth blocks and more delicate Weighted Template matching with Exponentially distributed weights (WTE) method was used to conceal texture blocks. The experimental results show that, compared with the WTE method, the proposed method has improved the Peak Signal-to-Noise Ratio (PSNR) by the average of 2.6 dB and decreased the computation complexity averagely by 90%. As for video sequences with different features and resolutions in continuous scene, the proposed method achieves certain applicability.

In view of the problem that high definition stereoscopic video sequences have high resolution, less information of macro block, and network transmission error, an end-to-end transmission distortion model was proposed. Considering error diffusion between frames caused by packet loss and the characteristics of spatial and temporal correlation, the recursive algorithm could estimate distortion accurately. And the error concealment method of copying the previous one of the lost frame was mainly used in the model, reducing the dependencies of the decoder. The simulation results show that the average prediction error of the distortion model can be controlled within 6%, and this model can be adapted to estimate transmission distortion for stereo video sequences with different features and resolutions under different network environments.