影像縮放於H.264編解碼應用之研究

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姓名

林姿宜(Tzu-Yi Lin) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

影像縮放於H.264編解碼應用之研究
(Video Downscaling for H.264 CODEC Application)

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摘要(中)

從高畫質的數位電視到個人隨身攜帶的手機，越來越多支援視訊播放功能的裝置已被人們廣泛使用，為讓視訊能更普遍地在各裝置間相互流傳，適當地調整視訊尺寸的大小以符合裝置的設定顯然是勢在必行。本論文提出以有限長度之升餘弦函數來作影像縮放的想法，並實證其效能優於傳統常用的雙立方、雙線性等函數。再者，本論文也針對影像縮減應用於H.264低位元率的情況作了分析，並得出將欲傳送的視訊縮減為原來一半再用H.264簡單畫面間預測模式編碼，其無論是在編碼時間或畫面品質的效能表現上都相當優異的結論。

摘要(英)

More and more devices that support video broadcasting like high definition television (HDTV) or mobile handsets have gained popularity in the world. In order to enable multimedia content to transfer between networks and devices, video rescaling techniques are needed. In this paper, we propose to use truncated raised cosine function for video rescaling. Experimental results reveal that the performance of truncated raised cosine interpolator is superior to that of widely used interpolator like Bicubic or Bilinear. Furthermore, we discuss video downscaling influence under low bit rate constraint for H.264 CODEC. The result shows that downscaling video size to the half before encoding this video with simple H.264 inter prediction mode will get best performance when comparing to other combinations.

關鍵字(中)

★ 影像縮放
★ H.264簡單畫面間預測模式
★ 低位元率
★ 升餘弦函數

關鍵字(英)

★ low bit rate
★ simple H.264 inter prediction mode
★ raised cosine function
★ video rescaling

論文目次

第一章緒論
1.1 簡介 1
1.2 研究動機 2
1.3 論文架構 3
第二章影像縮放原理及H.264編解碼介紹
2.1 影像縮放基本原理 4
2.2 基於影像縮放之畫面失真 7
2.3 H.264編解碼簡介 9
2.3.1 H.264編碼器 9
a. 畫面內(intra)預測模式 9
b. 畫面間(inter)預測模式 12
2.3.2 H.264解碼器 16
第三章升餘弦(Raised Cosine)應用於影像縮放之研究
3.1 理想影像插值器 17
3.2 傳統影像插值法簡介 20
3.2.1 最近相鄰(Nearest-Neighbor)內插法 20
3.2.2 雙線性(Bilinear)內插法 22
3.2.3 雙二階(Biquadratic)內插法 24
3.2.4 雙立方(Bicubic)內插法 24
3.3 升餘弦插值法 27
3.3.1 升餘弦基本介紹 27
3.3.2 升餘弦插值法之性能探討 30
3.4 各種插值法之效能比較 34
3.4.1 計算複雜度 34
3.4.2 影像品質 35
3.4.3 加入編解碼因子之效能表現 43
3.5 結論 50
第四章影像縮減應用於H.264低位元率視訊編解碼之探討
4.1 針對影像尺寸變換因素之探究 52
4.1.1 基於畫面內預測模式 53
4.1.2 基於畫面間預測模式 57
4.2 簡單畫面間預測模式效能分析 61
4.2.1 複雜型與簡單型畫面間預測模式比較 61
4.2.2 影像縮減與編碼預測模式交互影響之探討 65
4.3 運用畫面群(GOP)概念之高頻資訊補償模型 70
4.3.1 畫面群概念介紹 71
4.3.2 視訊影像高頻重建修正 72
4.3.3 基於畫面群之高頻補償演算法 74
4.4 結論 77
第五章結論與未來展望 78
參考文獻 79

參考文獻

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指導教授

林銀議(Yinyi Lin)

審核日期

2009-7-14

推文