把低解析度的影像轉換高解析度的技術是為影像內插。傳統的影像內插技術如雙線性內插及雙三次內插會在邊緣造成模糊及鋸齒狀的視覺缺陷。現行的方法減輕了傳統方法在邊緣造成的視覺缺陷。然而，現行的方法仍會在影像結構複雜的區域產生不自然的視覺效果且需高運算量。本研究提出使用空間與結構資訊結合雙線性內插法及雙三次內插法做為影像放大的解決方案。我們首先利用索貝爾邊緣偵測來從影像中區分出邊線區及非邊線區。對於邊線區的部分，我們估算出該邊線的角度，而後根據其角度旋轉該補償點與周圍參考點的空間幾何座標。接著利用旋轉後的距離與雙線性內插法或雙三次內插法內插該補償點。然後在內插時藉著伸長或縮短幾何距離以強調距離對內插的重要性。最後我們針對其角度上無參考點的補償點加以調整。為此，我們從垂直方向上的參考點而歸納出兩種邊線以補償該點。根據實驗結果，我們所提出的影像放大技術在視覺效果、評比數據及運算量這些方面皆較好。

Image interpolation is a technology for image resolution conversion that generates a high-resolution image from its given low-resolution image version. An ideal interpolation scheme should always go along the directions of the edge areas to prevent blurring and preserve the smoothness. The traditional interpolation techniques such as bilinear and bicubic interpolations tend to suffer from some problems such as blurring and jagging around the edges. The present methods were less blurring and jagging around the edges than traditional method. Therefore, some present methods improve the quality of edge region. However, the present methods still have some disadvantages such as extra artifact and high computation cost. This study proposes a hybrid approach that integrates the spatial and structure block-based information of an image into the basic kernel such as the bilinear or bicubic algorithm for image interpolation. The sobel edge detection method is utilized to separate the pixels of the input images into edge and non-edge regions. For the non-edge regions, the original tradition interpolation kernels such as bilinear and bicubic were used. For the edge regions, the spatial coordinates are rotated according to the estimated edge angle to calculate the spatial distances between the supplementary pixels and their neighbor pixels. And then the new distance be stretched or shrunk to highlight the importance of spatial distances. Finally, we conclude two types of edge by the structure information and use these types to compensate supplementary pixels without the reference pixels along the edge direction. According to the experiment results, the proposed method has a higher quantitative and qualitative performance, and lower computation cost than the modern edge-directed approaches.

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