Ultrahigh-resolution video-oriented coding unit partitioning optimization method

Abstract

The invention discloses an ultrahigh-resolution video-oriented coding unit partitioning optimization method. The method comprises the following steps: respectively setting a corresponding image texture complexity threshold value for each of coding units of different sizes; for each coding unit i, calculating a difference value between each pixel in the coding unit i and a pixel mean value of the coding unit i, and taking a sum of all the difference values as an image texture complexity of the coding unit i; if the image texture complexity of the coding unit i is less than or equal to the imagetexture complexity threshold value corresponding to the coding unit i, taking the coding unit i as an optimal coding unit, and outputting the optimal coding unit; otherwise, dividing the coding uniti, calculating the image texture complexity of each divided coding unit, if the image texture complexity is less than or equal to the corresponding image texture complexity threshold value, taking thecoding unit as the optimal coding unit, and outputting the optimal coding unit; otherwise, continuously dividing the coding unit; and when a depth value h reaches a set threshold value, determining the optimal coding unit by adopting an HEVC (High Efficiency Video Coding) algorithm, and outputting the optimal coding unit.

Description

technical field [0001] The invention relates to the field of computer image coding, in particular to a coding unit division optimization method for ultra-high-definition video. Background technique [0002] With the development of science and technology and the advent of the era of large screens, traditional high-resolution images can no longer meet the increasing visual needs of the public. The broadcasting media industry is also pursuing more perfect and clear images and accelerating the improvement of video resolution. Therefore, Ultra-high-definition video has gradually become a development hotspot. [0003] Compared with high-definition video, ultra-high-definition video has many advantages. It has higher resolution and larger data volume. The color allows the audience to get a more immersive feeling. [0004] However, the large increase in data volume also makes ultra-high-definition video face great difficulties in data transmission and data storage. In order to ens...

AI Technical Summary

Problems solved by technology

Compared with the previous coding standards, the HEVC coding standard has greatly increased computational complexity, and the coding time required for coding ultra-high-definition video sequences is too long, and most of the current optimization algorithms based on the HEVC coding standard are oriented to ordinary high-definition videos. Well combined with the characteristics of ultra-high-definition video

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