數位影像無論在傳輸、處裡或資料儲存上都有很多的優點。然而，因為來源影像的解析度有很多種，但使用者的數位顯示裝置解析度則是固定的，所以需要使用優異的影像縮放技術來解決不同解析度間的轉換。

本論文提出兩個影像縮放技術。第一個方法處裡的對象是交錯式的輸入影像，我們以ELA演算法為基礎，但使用一個更準確的方式來判斷影像邊緣的方向，以提高影像的品質。第二個方法主要是用來縮放非交錯式的影像訊號，它改良自傳統的 winscale 演算法，利用變型面積法（warped area method）和像素的差值來計算出新的像素值。實驗結果顯示我們的方法不論是在主觀上或是客觀上的評估都比傳統的演算法都好，尤其是在影像的邊緣部份更是有優異表現。此外，它們都易於實做，我們分別提出此二法的VLSI架構。模擬數據顯示，法一可以達到294MHMz，法二則可以達到56.75MHz 的工作頻率。

Digital image has many benefits in transmitting, processing and storing the image data. The resolutions of source images are different and the physical screen resolution of a digital display device is fixed, so the development of an excellent image scaling technique is necessary and inevitable.

We present two image scaling methods in this thesis. The first algorithm is proposed for the interpolation of interlaced images. On the basis of the ELA algorithm, a more efficient approach is adopted to detect correctly the edge direction. The second algorithm is proposed for scaling images which are not interlaced. Based on the winscale algorithm, we use the warped area method and pixel difference to calculate the interpolated pixels. Experiment results show that the proposed method outperforms other traditional algorithms in both subjective and objective quality measurements, especially in edge region. The VLSI architectures of the two methods are developed. In the simulation, the clock frequency of the first method achieves 294 MHz and the second one achieves 56.75 MHz, respectively.

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