| 研究生: |
林玉峰 Yu-Fong Lin |
|---|---|
| 論文名稱: |
適用於在離散餘弦轉換域中降低空間解析度的視訊轉碼器之低複雜度移動向量精練演算法 Video Transcoder in DCT-Domain Using Low Complexity Motion Vector Refinement Algorithm for Spatial Resolution Reduction |
| 指導教授: |
蔡宗漢
Tsung-Han Tsai |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
資訊電機學院 - 電機工程學系 Department of Electrical Engineering |
| 畢業學年度: | 93 |
| 語文別: | 英文 |
| 論文頁數: | 69 |
| 中文關鍵詞: | 離散餘弦轉換域之向量補償 、移動向量 、視訊轉碼器 |
| 外文關鍵詞: | MC-DCT, motion vector, video transcoding |
| 相關次數: | 點閱:10 下載:0 |
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近年來各種多媒體的服務造成正快速的成長,而這使得對數位視訊的需求量增加,例如:視訊遠距教學、視訊監控系統等等…。在這些多媒體的應用中,數位視訊壓縮是一重要的腳色。而對於各種多樣化的多媒體服務往往會由於不同的網路限制而要求不同的Bit-Rate。除此之外,一些客戶端設備的限制也決定了對各種不同視訊壓縮規格的需求。於現今的技術中,數位視訊轉碼器可以允許使用者快速的將之前已壓縮好的數位視訊資料轉換為另外一種格式以符合各種不同應用的需求。
在這篇論文中我們主要探討的問題是在離散餘弦轉換域中降低空間解析度的視訊轉碼器。在此提出了技術包含,階層式的快速移動向量產生(HFMR)已產生更精準的移動向量、低複雜度的快速的精鍊非整數的移動向量法(FRNI)與動態調整搜尋法(DRS)。兩種不同的精煉移動向量演算法是設計於不同的視訊轉碼架構之上分別適用於不同的需求。基於brute-force MC-DCT,我們提出使用快速的精鍊非整數的移動向量以增加整體的壓縮品質相對於未精練的移動向量並減少運算複雜度。而動態調整搜尋法則是基於利用半精準移動向量的MC-DCT與有效率的方法於萃取離散餘弦轉換域方塊在MC-DCT中以便更進一步的增進整體效能。
從實驗結果中我們可以清楚地了解到我們所提出的各種演算法都能非常有效率的增進數位視訊壓縮的品質與降低其運算複雜度於離散餘弦轉換域的視訊轉碼器上。
Recently, the masses have brought up all kinds of multimedia services to more and more demands of digit video, such as video on demand, distance learning and video surveillance. In these applications, compressed digital video is a major component of the multimedia data. Those various multimedia services demand different bit-rates to adapt network limitations and diverse terminal constraints decided by user. Among these techniques, video transcoding has allowed user to convert a previously compressed bit-stream into another format to meet various multimedia services.
In this thesis, we address in the topic of spatial-downscaling video transcoder in DCT domain. The proposed techniques include the Hierarchical Fast Motion Resampling (HFMR) with accuracy motion resampling, the Fast Refinement for Non-Integral-MV (FRNI) and the Dynamic Regulating Search (DRS) with low complexity motion vector refinement. Two kinds of motion vector refinement algorithms are design for different architectures and applications. Based on brute-force MC-DCT (Motion Compensation in DCT-Domain), FRNI can provide better quality than non-refine motion vector and reduce the complexity. DRS can utilize the filter for half-pixel motion vector in MC-DCT and efficient method for extracting MC-DCT block to improve the performance further.
From the experiments we have conducted, we believe that our proposed algorithms can improve the entire quality and also reduce the complexity for DCT-Domain video transcoder.
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