影像處理演算法藉由修改原始圖像像素的強度，可以將影像的形狀、紋理、邊緣和其他重要影像特徵作增強。此類演算法可以應用在許多顯示設備上，例如筆記型電腦，掌上電腦，顯示器，照相手機...等。
在一般情況下，影像處理演算法必須針對視訊影像的每一張畫面重新計算，因此提高了視頻處理應用的複雜性。

為了維持視訊影像處理品質，並進一步縮短處理時間，本論文提出了一種基於視頻編解碼標準擷取之運動向量的效能增強演算法。
運動向量是藉由尋找畫面中每一個marcoblock在目前畫面與參考畫面之間的距離而得的偏移量。
當前一張畫面和本張畫面只有些許改變時，藉由分析運動向量的數量可以簡化視訊影像處理演算法另一方面當畫面出現很大變化時也能維持視訊增強的品質。

我們將所提出的方法實作在H.264聯合模型參考軟體(JM 17)上，並藉由峰值訊噪比(PSNR)及程式執行時間分別驗證了我們提出方法能有效提供良好的視訊增強品質避免過度失真並且進一步降低計算複雜度。

Image processing methods involve modifying the intensity of pixels from the original image to represent the shape, texture, edge, and other significant features for many display devices, including laptops, PDAs, monitors, mobile camera phones, and so on. In general, image processing methods should be applied to every frame of a sequence, thus increasing the complexity of video processing applications.

In order to keep the processing effect and reduce the processing time, this thesis proposes a performance enhancement method based on the extraction of motion vectors in video codec standards. Motion vector is offset between the position of the current partition and the prediction region in the reference picture, calculated by finding matching blocks in the current frame corresponding to blocks in the reference frame. Analysing the amount of motion vectors can simplify the image processing methods when the current frame only changes a little, while presenting the original processing effect during the current frame which has great contextual change in the video sequence.

The proposed performance enhancement method is implemented by using MVs of the H.264 Joint Model reference software (version JM 17.0). Experimental result uses PSNR and processing time to demonstrate the effectiveness of the proposed method in providing the processing effect without serious distortion and low computational cost.

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