Aiming at the high complexity problem of inter-frame coding for screen content video, a fast inter-frame algorithm based on temporal-spatial correlation was proposed. Firstly, the encoding frames were classified to static frames and motion frames according to motion-static detection algorithm. Then, different encoding strategies were used for motion and static frames, respectively. For the static frames, the optimal partition depth and the optimal prediction mode of Coding Unit (CU) were determined based on the CU partition depth and the prediction mode of the temporal correlation. For the static Largest CU (LCU) in the motion frames, the CU partition was terminated prematurely by using the temporal correlation, and the mode selection was only for the large size modes. Whereas for the motion LCU in motion frames, the motion-static characteristic of adjacent LCU was utilized to determine the current CU partition depth and prediction mode. The experimental results show that the proposed method can reduce the average coding time by 46.40% when BDBR is increased by 3.65% compared with the original coding platform. The proposed method can significantly reduce the complexity of screen content inter-frame encoding process in the premise of negligible BDBR (Bjøntegaard Delta Bit Rate) performance loss. Therefore the proposed method is beneficial to the real-time application of screen content video.

In order to reduce the encoding complexity of the emerging High Efficiency Video Coding (HEVC), a fast hierarchical algorithm based on texture property and spatial correlation for intra coding was proposed. Firstly, Largest Coding Unit (LCU) level fast algorithm was adopted. The prediction depth of current LCU was derived by weighted prediction using the depth level of neighboring LCUs; the texture complexity of current LCU was determined by means of standard deviation and the strategy of adaptive threshold. Therefore, the Most Probable Depth Range (MPDR) of current LCU could be predicted by combining the prediction depth with the texture complexity of current LCU. Secondly, using Coding Unit (CU) level Depth Decision Fast Algorithm (CUDD-FA), combining the strategy of early decision of CU depth level based on edge-map with early termination of CU depth based on Rate Distortion (RD) cost correlation, the depth level of CU was determined before coding, and the complexity of intra coding process was further reduced. The experimental results show that, compared with the original HEVC encoding scheme, the proposed method reduces encoding time by an average of 41.81%, while the BD-rate (Bjøntegaard Delta bit rate) only increases by 0.74% and the BD-PSNR (Bjøntegaard Delta Peak Signal-to-Noise Rate) only decreases by 0.038 dB; compared with the representative literature algorithms, the proposed algorithm achieves better RD performance with saving more encoding time. The proposed method can significantly reduce the complexity of intra coding process in the premise of negligible RD performance loss, especially for video sequences with high resolution, which is beneficial to the real-time video applications of HEVC standard.

As the main scheme of 3D scene representation, multiview video plus depth attracts more and more attention. Depth video reflects the geometric information of the scene. It is important to design fast depth video encoding algorithm. A fast depth video coding algorithm based on region division was proposed. Firstly, the depth video was divided into four regions according to the features of edge and motion. Then, macroblock distribution proportion and multi-reference frame selection feature of different regions were analyzed. Consequently, different macroblock mode decision and reference frame selection methods were utilized to speedup depth video encoding. Finally, some experiments were conducted to estimate the proposed algorithm in terms of encoding time, bit rate and virtual view quality. Experimental results show that the proposed algorithm saves encoding time ranging from 85.73% to 91.06% while it maintains virtual view quality and bit rate.