本文提出一應用於高解析度影像放大的疊代內插演算法，其根據內插像素的座標與鄰近的像素關係，採用疊代內插或進行邊緣偵測再內插。本文在邊緣偵測器之中加入了由實驗得到的臨界值，以此將內插分為有方向性與無方向性內插。方向性內插主要用以避免在高頻訊號方向進行內插而產生模糊影像，疊代內插與無方向性內插則用以處理低頻訊號，內插的權重是由立方內插函數經過化簡與調整參數而得，其進行低頻訊號內插時獲得的效果比雙立方內插函數還好。
當輸入的影像大小為176×144，輸出的影像大小為352×288時，本文的訊雜比可提升0.1dB到0.2dB。當輸入的影像大小為1920×1080，輸出的影像大小為3840×2160時，訊雜比可提升0.05dB。並且不論是低解析度還是高解析度影像，本文的結構相似度都是最接近1，優於其他內插方法。

This article proposes an iterative interpolation algorithm for upsampling super resolution images. The algorithm using iterative interpolation or edge detecting before interpolation according to the coordinate of input pixels and the relationship of nearby pixels. To divide the interpolation into directive and none directive interpolation this article adding a threshold value in the edge detector. The directive interpolation is used to prevent image blurred when interpolate in the high frequency domain. Iterative interpolation and none directive interpolation are used to process low frequency signal and the weighting function of interpolation is generated from simplify and adjust the parameter of cubic interpolation which the result was better than bicubic interpolation when interpolate in the low frequency domain.
When the input image size is 176 by 144 and the output image size is 352 by 288 the PSNR can be improved 0.1dB to 0.2dB. When the input image size is 1920 by 1080 and the output image size is 3840by2160 the PSNR can be improved 0.05dB. The result of structure similarity of the proposed method is better than the other method.

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