本論文提出一個用於高解析度的局部紋理強化之三邊濾波器。此系統主要包括利用三邊濾波器回歸進行內插與局部紋理強化兩部分。三邊濾波器主要是用來改善傳統NEDI方法的缺點。在內插部分，利用三邊濾器給予在訓練區塊裡的每個像素適當的權重。因此，便會減少某些區域的區塊效應。並在內插後於部分紋理區域加上高頻率的資訊，達到改善紋理模糊的問題。
實驗結果的部分，從客觀的評價來看，本論文所提出的三邊濾波器比數種目前知名的方法有更高的PSNR與SSIM的表現。除此之外，局部紋理強化也在主觀的觀察者給予的評分裡獲得較高的視覺表現。

In this thesis, a super resolution using trilateral filter regression with local texture enhancement is proposed. The system consists of two major parts, the interpolation of trilateral filter regression, and local texture enhancement. The trilateral filter is used to fix the disadvantage of the traditional NEDI methods. In the interpolation part, the suitable weights are given for all pixels in the training window by the trilateral filter. Hence, the blocking effect can be reduced in some regions. After interpolations part, the high frequency information of the local texture is added into the enlarged images to improve the texture blurring.
Experimental results demonstrate that the proposed method provides superior performance than other well-known approaches in the average PSNR and SSIM. In addition, the texture enhancement achieves better subjective performance by evaluation of observers.

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