Efficient Depth Decision for Coding Units based on Adaptive Weight

碩士 === 國立臺灣科技大學 === 資訊工程系 === 101 === The state-of-the-art video codec, high efficiency video coding (HEVC), adopts quadtree-structured coding units (CUs) for efficient compression of high resolution video sequences. However, at the encoder side, motion estimation (ME) for the CUs in each quadtree-s...

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Main Authors: SHENG-CHIEH LIN, 林聖杰
Other Authors: Kuo-Liang Chung
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/37194529236742244695
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spelling ndltd-TW-101NTUS53920692016-03-21T04:28:03Z http://ndltd.ncl.edu.tw/handle/37194529236742244695 Efficient Depth Decision for Coding Units based on Adaptive Weight 植基於可調式權重的有效編碼單元之深度決定 SHENG-CHIEH LIN 林聖杰 碩士 國立臺灣科技大學 資訊工程系 101 The state-of-the-art video codec, high efficiency video coding (HEVC), adopts quadtree-structured coding units (CUs) for efficient compression of high resolution video sequences. However, at the encoder side, motion estimation (ME) for the CUs in each quadtree-structured depth level should be preformed to find the optimized rate-distortion depth level, resulting in extremely high computational complexity. In this thesis, we propose an efficient CU depth level decision algorithm based on adaptive weight mechanism. By utilizing the residuals and depth levels of neighboring CUs in the current frame and co-located CU in the previous frame, the proposed algorithm can adaptively determine an appropriate depth level range for the current CU. Since ME process is only performed in the determined depth level range rather than all the depth levels, it leads to significant reduction of computational complexity. Experimental results demonstrate that the proposed algorithm can significantly reduce computational complexity while preserving quite similar quality of the reconstructed video sequences to that by standard HEVC encoder. Furthermore, when compared with Shen et al.'s method, the proposed method has some benefit on reducing bitrate and encoding time. Kuo-Liang Chung 鍾國亮 2013 學位論文 ; thesis 25 zh-TW
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description 碩士 === 國立臺灣科技大學 === 資訊工程系 === 101 === The state-of-the-art video codec, high efficiency video coding (HEVC), adopts quadtree-structured coding units (CUs) for efficient compression of high resolution video sequences. However, at the encoder side, motion estimation (ME) for the CUs in each quadtree-structured depth level should be preformed to find the optimized rate-distortion depth level, resulting in extremely high computational complexity. In this thesis, we propose an efficient CU depth level decision algorithm based on adaptive weight mechanism. By utilizing the residuals and depth levels of neighboring CUs in the current frame and co-located CU in the previous frame, the proposed algorithm can adaptively determine an appropriate depth level range for the current CU. Since ME process is only performed in the determined depth level range rather than all the depth levels, it leads to significant reduction of computational complexity. Experimental results demonstrate that the proposed algorithm can significantly reduce computational complexity while preserving quite similar quality of the reconstructed video sequences to that by standard HEVC encoder. Furthermore, when compared with Shen et al.'s method, the proposed method has some benefit on reducing bitrate and encoding time.
author2 Kuo-Liang Chung
author_facet Kuo-Liang Chung
SHENG-CHIEH LIN
林聖杰
author SHENG-CHIEH LIN
林聖杰
spellingShingle SHENG-CHIEH LIN
林聖杰
Efficient Depth Decision for Coding Units based on Adaptive Weight
author_sort SHENG-CHIEH LIN
title Efficient Depth Decision for Coding Units based on Adaptive Weight
title_short Efficient Depth Decision for Coding Units based on Adaptive Weight
title_full Efficient Depth Decision for Coding Units based on Adaptive Weight
title_fullStr Efficient Depth Decision for Coding Units based on Adaptive Weight
title_full_unstemmed Efficient Depth Decision for Coding Units based on Adaptive Weight
title_sort efficient depth decision for coding units based on adaptive weight
publishDate 2013
url http://ndltd.ncl.edu.tw/handle/37194529236742244695
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