Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/7813
標題: 適用於低位元率視訊壓縮之改良式物件方塊向量搜尋法
An Modified Objected Block-Base Vector Search Algorithm for Low Bit-Rate Video Coding
作者: 劉宇倫
Liou, Yu-Luen
關鍵字: Modified objected block-based search algorithm;改良式物件方塊搜尋演算法;predictive search algorithm;mean absolute error;motion estimation;預測式搜尋演算法;平均絕對值誤差;移動估計
出版社: 電機工程學系
摘要: 
在即時性的動態影像壓縮及傳送中,移動估計對傳輸效率及壓縮率的影響非常的大,為了提高移動向量尋找的速度,我們以物件方塊向量搜尋法為基礎,觀察中央區塊與全畫面變化的關係,提出改良的方法,利用中央區塊在兩個畫面之間的平均絕對值誤差變化作為改變更新數量的指標,並用中央區塊的移動向量大小設定不同的門檻值,若指標值大於門檻值則降低更新數量;反之,則增加更新數量。模擬的結果顯示,使用本演算法相對於原來的方法在預測式搜尋法上運算量平均可以比原先降低5.22%,在峰值訊雜比提升0.1174%。不論在速度或品質都更勝一籌。因此,本演算法可以提供作為即時影像壓縮編碼器中移動向量搜尋演算法的新選擇。

Motion estimation plays an important role in real-time video compression and transmission. In order to improve searching speed of motion vector, we have developed a modified objected block-base Search (MOBS) algorithm. The algorithm is based on the observation that the variation of mean absolute error in the current frame and the mean absolute error in the center block of current frame. The variation the motion vector of central blocks can be used as an index to refresh the value of update number and set up for different threshold. If the value exceeds the threshold, the refresh number is decreased; if not then increases the refresh number. The simulation result shows using the MOBS algorithm can have 5.22% faster than using the object based search (OBS) algorithm. On the other hand, the peak-to-signal noise ratio (PSNR) of the MOBS algorithm is 0.1174% faster than the OBS algorithm.
URI: http://hdl.handle.net/11455/7813
Appears in Collections:電機工程學系所

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