Fast three‐dimensional video coding encoding algorithms based on edge information of depth map

Abstract

The high-efficiency video coding (HEVC) standard for three-dimensional (3D) video, which is called 3D-HEVC, improves the compression efficiency for high resolution 3D video sequences. In this study, three coding time reduction algorithms, namely fast coding unit partition, fast prediction unit (PU) partition and search range reduction, are proposed for inter-prediction of 3D-HEVC by referring to the depth edge information. The pixels in one object should have the same motion characteristics. By detecting depth edge, we can easily classify the regional pixels if they are in the same object. Thus, in the encoding stage, the sizes of coding and PUs can be determined by the proposed fast coding unit partition and fast PU partition methods, respectively. Furthermore, the range of motion search can be effectively reduced by the proposed search range reduction method. Experimental results show that the proposed depth edge-based motion search algorithms can reduce the coding time of inter-prediction by up to 62% on average with negligible quality degradation.

Vision‐oriented algorithm for fast decision in 3D video coding

“…The performance comparison of the structural similarity index measure(SSIM) is shown in Table 15. The △SSIM of proposed method is only −0.000057 on average and is better than the −0.000060 of [30]. It verifies the robustness of the proposed method on video quality.…”

“…The details of the experimental environment and test sequences are listed in Tables 10 and 11, respectively. To fairly verify our approach, we also implement the work in [30] with the same configuration settings and compare the coding performance of our method to [30].…”

“…The fast asymmetric motion partitioning in [29] roughly determines the PU partition types by nine-point inspection. The line- based PU partitioning in [30] coarsely switches the PU modes by the vertical and horizontal detecting lines. However, there is still room for improving the prediction accuracy through a more comprehensive consideration.…”

“…The fast PU partitioning scheme in [29] has the line-based, block-based, and nine-point edge inspections to accelerate the inter prediction for both colour texture and depth map. In [30], fast CU/PU partitioning and search range reduction (CP2AS) was proposed based on the edge information from Canny edge detector. Once there is less edge information within current coding CU, the search range of the prediction will be modified and CU further splitting is not allowed.…”

A Comparative Study on the Method of Extracting Edge and Contour Information of Multifunctional Digital Ship Image

“…Human vision is usually through the target object's edge and contour [1], to distinguish the target objects [2][3], whereas in the multifunctional digital ship image, the edge is an important feature that distinguishes different regions [4][5]. The edge and contour information of multifunctional digital ship image refers to the part of that the local brightness changes significantly [6], it exists between the target image and another target image [7], the target image and background image, the regional image and another regional image [8][9].…”