Browsing by Author "Wang, Chung-Neng"

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A multiple-window video embedding transcoder based on H.264/AVC standard
(2007)
Li, Chih-Hung
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Wang, Chung-Neng
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Chiang, Tihao
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
This paper proposes a low-complexity multiple-window video embedding transcoder (MW-VET) based on H.264/ AVC standard for various applications that require video embedding services including picture-in-picture ( PIP), multichannel mosaic, screensplit, pay-per-view, channel browsing, commercials and logo insertion, and other visual information embedding services. The MW-VET embeds multiple foreground pictures at macroblock-aligned positions. It improves the transcoding speed with three block level adaptive techniques including slice group based transcoding (SGT), reduced frame memory transcoder (RFMT), and syntax level bypassing (SLB). The SGT utilizes prediction from the slice-aligned data partitions in the original bitstreams such that the transcoder simply merges the bitstreams by parsing. When the prediction comes from the newly covered area without slice-group data partitions, the pixels at the affected macroblocks are transcoded with the RFMT based on the concept of partial reencoding to minimize the number of refined blocks. The RFMT employs motion vector remapping (MVR) and intra mode switching (IMS) to handle intercoded blocks and intracoded blocks, respectively. The pixels outside the macroblocks that are affected by newly covered reference frame are transcoded by the SLB. Experimental results show that, as compared to the cascaded pixel domain transcoder (CPDT) with the highest complexity, our MW-VET can significantly reduce the processing complexity by 25 times and retain the rate-distortion performance close to the CPDT. At certain bit rates, the MW-VET can achieve up to 1.5 dB quality improvement in peak signal-to-noise-ratio (PSNR). Copyright (C) 2007 Chih-Hung Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
A NMR optimized bitrate transcoder for MPEG-2/4 LC-AAC
(2007)
Lai, Te-Hsueh
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Wang, Chung-Neng
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Chiang, Tihao
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交大名義發表
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National Chiao Tung University
This paper presents a noise-to-making-ratio (NMR) optimized MPEG-2/4 AAC Low-Complexity (LC) transcoder, called as Fast Rate-Distortion Optimized Transcoder (FRDOT). The FRDOT searches for the optimal scalefactors under the NMR criterion according to the magnitudes of quantized input coefficients and the target bitrate. The computation of NMR difference is replaced by the derivation of signal-to-noise-ratio (SNR) difference since the audible masking thresholds of the original and transcoded bitstreams are identical. The SNR value is further converted to a noise-to-signal-ratio (NSR) to represent distortion energy of audio signals. With the NSR values, a table lookup technique is used to speed up the search of the optimal scalefactor increment. To further reduce the execution time, a bandwidth limiter is used to remove the iterative rate-distortion optimization of a frame. In addition, a bitrate control module is proposed to make the averaged bitrate of output bitstream close to the target bitrate. The results show that the FRDOT has smaller NMR values than the cascaded transcoder (CT) by 0.5-3.0 dB at different bitrates with 6-7 times speedup on the average.
Architecture for stack robust fine granularity scalability
(2005-09-08)
Huang, Hsiang-Chun
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Wang, Chung-Neng
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Chiang, Tihao
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Hang, Hsuch-Ming
The present invention relates to an architecture for stack robust fine granularity scalability (SRFGS), more particularly, SRFGS providing simultaneously temporal scalability and SNR scalability. SRFGS first simplifies the RFGS temporal prediction architecture and then generalizes the prediction concept as the following: the quantization error of the previous layer can be inter-predicted by the reconstructed image in the previous time instance of the same layer. With this concept, the RFGS architecture can be extended to multiple layers that forming a stack to improve the temporal prediction efficiency. SRFGS can be optimized at several operating points to fit the requirements of various applications while the fine granularity and error robustness of RFGS are still remained. The experiment results show that SRFGS can improve the performance of RFGS by 0.4 to 3.0 dB in PSNR.
Fast motion estimation using N-queen pixel decimation
(2003-07-03)
Chiang, Tihao
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Liu, Chi-Min
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Wang, Chung-Neng
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Yang, Shin-Wei
The present invention proposes a fast motion estimation using N-queen pixel decimation, whereby after a reference block and a block to be processed are selected in a video sequence, an N×N queens pattern is used for pixel decimation to perform block match, thereby obtaining a good enough block difference value. The present invention combines pixel decimation with fast motion estimation for search points reduction to achieve the object of simplifying computational complexity of motion estimation. Therefore, the present invention can sieve out sufficiently representative pixels and will not increase extra computational complexity.