消除雜訊與影像增強是影像處理的重要技術，許多影像處理應用需作影像平滑化或消除雜訊，但同時也要能保留影像線條，簡單的影像平滑化處理，例如高斯低通濾波器，通常會造成影像模糊。雙邊濾波器(bilateral filter)能延伸高斯平滑化方法，藉由使用局部適應性運算法則，其濾波係數是根據鄰近影像像素強度的權重比較，避免橫跨線條時作濾波平均，實質上它是使用非線性高斯濾波器的一種迴旋運算，非反覆性的雙邊濾波器能偵測保留影像之線條，只對位於線條同一邊的像素執行平均平滑作用，已有報告指出雙邊濾波器的一些應用結果優於線性濾波器，本論文將檢閱雙邊濾波器的運算法則、特性、與影像處理應用，也提出有關雙邊濾波器的實驗結果與評估研討。

Image denoising and contrast enhancement are important techniques in image processing. Many imaging applications require the image smoothing or denoising while preserving the detailed edges. Simple smoothing operations such as low-pass Gaussian filtering which does not consider intensity variations tend to create blurred images. Bilateral filtering (BF) extends the Gaussian smoothing technique by using a locally adaptive recovery algorithm. The filter coefficients are weighted with corresponding image pixel intensities. It is essentially a convolution process using a nonlinear Gaussian filter, with weights based on pixel intensities. The non-iterative bilateral filter can detect and preserve image edges and average only those pixels on the same side of an edge. It has been reported to have a better edge-preserving capability than linear filters in certain applications. This paper presents a review of the algorithm, characteristics, and imaging applications of the bilateral filter. Experimental results and evaluation study on the performance of bilateral filtering are also presented.