Title :
Block-level adaptive optimization for inter-layer texture up-sampling in H.264/SVC
Author :
Chang, Kan ; Qin, Tuanfa ; Zhang, Wenhao ; Men, Aidong
Author_Institution :
Sch. of Comput. & Electron. Inf., Guangxi Univ., Nanning, China
Abstract :
H.264 Scalable Video Coding (SVC) extension has spatial scalability which is able to provide various resolution sequences for a single encoded bit-stream. In order to reduce redundancies between different layers, for spatial scalable intra-coded frames, co-located reconstructed 8×8 sub-macroblock in base layer (BL) is up-sampled to predict the marcoblock (MB) in enhancement layer (EL). Unfortunately, simple 1-D poly-phase up-sampling filter used in current SVC isn´t cable of achieving ideal result, which limits the performance of inter-layer intra prediction (ILIP). This paper proposes an adaptive optimization method for inter-layer texture up-sampling by applying wiener filter and controlling it at block level. Working as an additional part of ILIP, the proposed method can greatly reduce the prediction error between the original EL signals and the up-sampled BL signals. Experimental results show that, the proposed method achieves bit rate reduction up to 14.25% and PSNR increment up to 0.97 dB when compared with the traditional method in current SVC.
Keywords :
Wiener filters; image texture; video coding; 1D poly-phase up-sampling filter; H.264 scalable video coding; H.264/SVC; Wiener filter; base layer; bit rate reduction; block-level adaptive optimization; enhancement layer; inter-layer texture up-sampling; interlayer intra prediction; prediction error; spatial scalable intra-coded frames; Filter banks; Filtering algorithms; Mathematical model; Optimization; PSNR; Static VAr compensators; Wiener filter;
Conference_Titel :
Multimedia Signal Processing (MMSP), 2011 IEEE 13th International Workshop on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4577-1432-0
Electronic_ISBN :
978-1-4577-1433-7
DOI :
10.1109/MMSP.2011.6093811