Dynamic 3D point cloud compression intra-frame CU rapid division method and device, and medium

Abstract

The invention discloses a dynamic 3D point cloud compression intra-frame CU rapid division method and device and a medium. The method comprises the steps that whether a current dynamic 3D point cloudcompression coding frame is an I frame or not is judged; if yes, a target coding CU needing to be compressed and coded is sequentially extracted, an original brightness pixel value of the target coding CU is obtained, and conversion is performed; when the width and the height of the target coding CU are 64, a first preset condition is satisfied; or, when the width and the height of the target coding CU are 32, a second preset condition is satisfied; or, when the width and the height of the target coding CU are 16 and a third preset condition is satisfied, further division of the target codingCU is stopped. According to the method, whether the target coding CU in the CTU is the optimal coding can be accurately predicted in advance, so that the complicated steps of a recursion division method are omitted or skipped, the coding quality of the target coding CU is further ensured, and the calculation complexity in the division process of the target coding CU is remarkably reduced.

Description

technical field [0001] The present invention relates to the technical field of point cloud compression, in particular to a method, device and medium for fast division of CUs within a dynamic 3D point cloud compression frame. Background technique [0002] The 3D point cloud uses the geometric information, color information, surface normal and other features in the real physical scene to reconstruct a realistic digital 3D scene, providing people with a visual experience from any angle. As a data form that can represent three-dimensional scenes, 3D point cloud has been gradually applied in the fields of virtual reality (Virtual Reality, VR), smart city, robotics and autonomous driving. 3D point cloud mainly includes static point cloud and dynamic point cloud. A dynamic 3D point cloud captured at a rate of 30 frames per second usually has 700,000 points per frame, and the transmission of uncompressed dynamic 3D point cloud data requires a network transmission rate of up to 500M...

AI Technical Summary

Problems solved by technology

However, although this exhaustive division strategy can improve the efficiency of compression coding, it also brings huge computational complexity of compression coding, which seriously hinders the real-time transmission of dynamic 3D point clouds.

In addition, since the geometry and color video generated by dynamic 3D point cloud mapping are very different from natural video, this will cause the proposed HEVC fast CU partition method for natural video to not work well for video-based dynamic 3D point Cloud compression coding optimization

At present, there is no effective solution to this problem

Images