本論文呈現一個使用影像結構及移動偵測之動態影像雜訊抑制濾波器，此濾波器被使用在抑制動態影像中的高斯雜訊。所提出的演算法是一個空間時間上的濾波器，它利用空間上和時間上的資訊去抑制雜訊，此濾波器利用影像結構及移動偵測去分析包含高斯雜訊的動態影像，此將能夠避免去除雜訊後所產生的不自然痕跡和模糊並保護空間上詳細資訊和移動的區域。此外所提出的演算法包含雜訊程度預測，因此所提出雜訊抑制演算法可以根據不同程度的雜訊去適應性地調節濾波器。結果顯示我們提出的濾波器在主觀的視訊品質和客觀的訊號雜訊比改善比較都有良好的效果。

This thesis presents a noise reduction filter for image sequences by using image structure and motion detection. We focus on reducing Gaussian noise in image sequences in this thesis. The proposed noise reduction filter is a spatiotemporal filter and it takes advantage of both the spatial and temporal information to reduce noise. In order to analyze the image sequences corrupted by Gaussian noise, this filter uses the technique of the image structure detection and motion detection. It would avoid inducing the artifacts and burring after noise reduction. The region of the spatial detail and motion is also preserved. Besides, because our proposed noise reduction algorithm includes the noise level estimation, the proposed noise reduction filter is adaptive according to the different noise level. The result shows that the performance of our proposed noise reduction filter is better than other methods in subjective visually quality and objective SNRi comparison.

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