本論文主要在探討如何使用模糊重力搜尋演算法來降低影像縮放時的不協調。影像內插法(Interpolation)區分兩種類型：單一影像與多重影像。前者多使用在圖片修復、重建與局部性放大檢視；而後者大多使用在視覺上，由於可連續取得即時影像，因此可以達到即時縮放效果。在影像縮放處理上，最難部分即是增加或維持影像的銳利度與平滑度，並降低產生的模糊感。
本文所提出的方法是利用傳統的線性(Linear)內插法做修改，使用模糊重力搜尋演算法(Fuzzy GSA)以求得最佳像素補償比例，即使在高倍率縮放時，仍然可以保有清晰的影像。在實驗模擬上，與傳統內插法做比較後，峰值信噪比(PSNR)較高以及影像表現有較佳效果。

This thesis aims to apply fuzzy gravitation search algorithms to decrease the image zooming inconsistent condition. The image interpolation method distinguishes between the two categories: single frame and multi-frame. The latter is often used in visually, due to the continuous access to live images, so a real-time zooming effect can be achieved. The former is mostly used in repair, reconstruction and local pictures to enlarge the view. In the image scaling process, the hardest part is to increase or maintain the sharpness and smoothness of the image and to reduce the blurring.
The proposed method is to modify the traditional linear interpolation method, and make use of the fuzzy gravitational search algorithm in order to achieve optimal compensation rate of pixel. Even if in high-magnification scaling, we still have a clear image. Simulation results demonstrate that the proposed scheme gives a higher peak-signal-to-noise ratio (PSNR) and shows a better images results in comparison with traditional method.

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