本論文提出一個用於突波雜訊移除之適應性中值影像濾波器，此濾波器特別適用於高雜訊的影像，且因為運算複雜度低，故非常適合以硬體來實現。一般而言，突波雜訊移除濾波器分成兩個部分：突波雜訊偵測(Impulse Noise Detection)與影像濾波(Image Filtering)。我的方法主要是針對突波雜訊偵測做改善，使用在遮罩中最暗與最亮的點與其之間的絕對差值來做突波偵測與降低誤判情況。大部分突波雜訊偵測效果都會隨著影像的突波雜訊比率增高而降低，我所提出的突波雜訊偵測效果會隨著影像中的雜訊比率增高而更好。在影像濾波部分，則是使用自適性中值影像濾波(Adaptive Median Filtering)來將前級所測出的雜訊濾除，產生無雜訊的影像。
實驗數據顯示，此法的未偵測率、誤判率都優於其他演算法。最後，我也設計此濾波器的硬體電路，並結合Leon3 Soft CPU，實作在FPGA模擬板上，成為一個SoPC的系統。

In this thesis, I propose an adaptive rank-ordered median image filter for removing salt-and-pepper noise. Our method is suitable for images corrupted highly and it can be implemented easily with hardware due to its low computation complexity. Generally speaking, the image filter performs two functions: the first is the impulse noise detection, and the other is the image filtering. The main focus of this thesis is impulse noise detection. We use the brightest and lightest pixels in the mask to decide the current pixel as impulse noise or not, and use the absolute difference value of brightest and lightest pixels to decrease the error-detection. If the noise-ratio in the image increases, the performance of most impulse noise detection methods will decreases. However, the proposed method achieves better performance even the noise-ratio is very high. At the second stage, we use the adaptive median filtering to remove impulse noise by using the noise information obtained in the previous noise-detection stage.
Based on the experimental results, we found the performance of un-detection ratio and error-detection ratio of the proposed method is better than other algorithms. Finally, we develop the hardware circuit for the proposed filter. By integrating with the Leon3 soft-IP processor, we implement the whole system on a FPGA emulation board.

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