A fast intra mode decision algorithm is proposed in this paper to reduce the complexity of H. 264 encoder. The proposed algorithm adopted the pre-processing method based on edge feature in pictures to filter out some ...A fast intra mode decision algorithm is proposed in this paper to reduce the complexity of H. 264 encoder. The proposed algorithm adopted the pre-processing method based on edge feature in pictures to filter out some impossible prediction modes. Context information and pre-computed threshold are used to determine whether it is necessary to check the DC mode. This method is able to get rid of most of candidate modes so that only 66--150 modes are left for the final mode decision, instead of 592 modes in the case of full search （FS） method of H. 264. Simulation results demonstrate that the coding time of the proposed algorithm falls down 71.7% compared with FS method, while the performance loss is trivial compared with FS mode decision scheme.展开更多
To decrease the computational complexity of adaptive inter-layer prediction and improve the encoding efficiency in sealable video coding, a mode decision algorithm is proposed by exploiting the part of used candidate ...To decrease the computational complexity of adaptive inter-layer prediction and improve the encoding efficiency in sealable video coding, a mode decision algorithm is proposed by exploiting the part of used candidate modes of the co-located reference macrobloeks for Hierarchical-B pictures. This scheme reduces the amount of the candidate modes to generate a dynamic list for the current encoding macroblock according to the statistical information derived from the co-located reference macroblocks in different temporal levels. The experimental results show that this fast algorithm reduces approximately 31% encoding time on average with the negligible loss of encoding performance.展开更多
In Video-based Point Cloud Compression(V-PCC),2D videos to be encoded are generated by 3D point cloud projection,and compressed by High Efficiency Video Coding(HEVC).In the process of 2D video compression,the best mod...In Video-based Point Cloud Compression(V-PCC),2D videos to be encoded are generated by 3D point cloud projection,and compressed by High Efficiency Video Coding(HEVC).In the process of 2D video compression,the best mode of Coding Unit(CU)is searched by brute-force strategy,which greatly increases the complexity of the encoding process.To address this issue,we first propose a simple and effective Portable Perceptron Network(PPN)-based fast mode decision method for V-PCC under Random Access(RA)configuration.Second,we extract seven simple hand-extracted features for input into the PPN network.Third,we design an adaptive loss function,which can calculate the loss by allocating different weights according to different Rate-Distortion(RD)costs,to train our PPN network.Finally,experimental results show that the proposed method can save encoding complexity of 43.13%with almost no encoding efficiency loss under RA configuration,which is superior to the state-of-the-art methods.The source code is available at https://github.com/Mesks/PPNforV-PCC.展开更多
文摘A fast intra mode decision algorithm is proposed in this paper to reduce the complexity of H. 264 encoder. The proposed algorithm adopted the pre-processing method based on edge feature in pictures to filter out some impossible prediction modes. Context information and pre-computed threshold are used to determine whether it is necessary to check the DC mode. This method is able to get rid of most of candidate modes so that only 66--150 modes are left for the final mode decision, instead of 592 modes in the case of full search （FS） method of H. 264. Simulation results demonstrate that the coding time of the proposed algorithm falls down 71.7% compared with FS method, while the performance loss is trivial compared with FS mode decision scheme.
基金Sponsored by the Fundamental Research Funds for the Central Universities(Grant No. HEUCF11805)
文摘To decrease the computational complexity of adaptive inter-layer prediction and improve the encoding efficiency in sealable video coding, a mode decision algorithm is proposed by exploiting the part of used candidate modes of the co-located reference macrobloeks for Hierarchical-B pictures. This scheme reduces the amount of the candidate modes to generate a dynamic list for the current encoding macroblock according to the statistical information derived from the co-located reference macroblocks in different temporal levels. The experimental results show that this fast algorithm reduces approximately 31% encoding time on average with the negligible loss of encoding performance.
基金supported by the National Natural Science Foundation of China(No.62001209).
文摘In Video-based Point Cloud Compression(V-PCC),2D videos to be encoded are generated by 3D point cloud projection,and compressed by High Efficiency Video Coding(HEVC).In the process of 2D video compression,the best mode of Coding Unit(CU)is searched by brute-force strategy,which greatly increases the complexity of the encoding process.To address this issue,we first propose a simple and effective Portable Perceptron Network(PPN)-based fast mode decision method for V-PCC under Random Access(RA)configuration.Second,we extract seven simple hand-extracted features for input into the PPN network.Third,we design an adaptive loss function,which can calculate the loss by allocating different weights according to different Rate-Distortion(RD)costs,to train our PPN network.Finally,experimental results show that the proposed method can save encoding complexity of 43.13%with almost no encoding efficiency loss under RA configuration,which is superior to the state-of-the-art methods.The source code is available at https://github.com/Mesks/PPNforV-PCC.
