Fast Depth Decision Algorithm Of Coding Unit In HEVC

With the development of mobile Internet and other emerging technologies, the demands on high quality video service are increasing, and the development of transmission medium is from online to wireless. High quality video requires an increase in the amount of video data to be processed. Transfer of a large amount of data over limited band width requires acceleration in the development of a video coding standard with high compression efficiency. Some international organization for standardization researched on video coding standard protocol, and released the next-generation video compression standard named HEVC standard in2013. HEVC is performed using all the possible depth levels and prediction modes to find the one with the least rate distortion cost, which can improve coding efficiency about50%. Compared with other standards, HEVC provides higher coding efficiency, leading to higher coding complexity however. Therefore, by optimizing the depth of coding unit to reduce the encoding complexity is a hot and difficult problem in the research of video compressing.In this paper, we propose a fast depth decision algorithm for coding unit in HEVC to reduce computational complexity by using the video temporal correlation and spatial correlation. From the aspect of depth decision for coding unit:first, we base on the temporal correlation of video sequences. By checking the depth information of co-locate CU, we can pre-determine the candidate CU depth. Then, we use the spatial correlation of video image. We determine whether the image of current coding unit is located in the edge region or with complex texture by checking the depth information of neighbor CU. If the image of current coding unit is located in the edge region or with complex texture, we will use the standard algorithm; else we will use the optimization algorithm to reduce the encoding complexity. From the aspect of intra prediction, because of the absolute transform difference can effectively predict the responses of the difference image and the original image. To compare the rate distortion cost between the most probable mode and the candidate modes, the number of candidate modes can be adaptively adjusted.The proposed algorithm predicts the depth range of coding unit and to optimize the intra prediction modes number by using the video temporal correlation and spatial correlation, it can significantly reduce computational complexity. Experimental results show that our proposed fast depth decision algorithm of coding unit in HEVC can save38.76%encoding time in all intra low complexity cases on average compare to the original HEVC intra coding in HM10.0. Meanwhile, the results are especially favorable with up to60.23%encoding time savings and0.07dB PSNR reducing when the video is vidyol. Thus, our algorithm is an effective method to reduce HEVC coding complexity.