这样，滤波时就可以考虑到图像的亮度信息，在滤除图像噪声的同时尽量保持了图像的边缘。
In this way, image brightness will be taken into account and the image edge should be simultaneously maintained as possible during filtering image noise.
实验结果表明，谊方法不但可以保持图像的边缘信息，而且能够提高去噪后图像的信噪比。
Experimental results showed that the algorithm could not only keep edge information of image, but also could improve signal-to-noise ratio of an image.
实验结果表明，该方法可以有效地抑制相干斑噪声，同时很好的保持边缘纹理信息。
Experimental results demonstrate that the proposed method can effectively suppress speckle noise, while preserving the edge and texture information.
本文利用图像的相关性原理，结合图像的边缘信息，提出了一种新的图像边缘保持的方向平滑算法。
In this paper, a new image's edge preserving orientation smoothing algorithm is proposed according to image's correlation theorem and edge characteristic information.
我们的主要目标是在去除图像噪声的同时尽可能地保持图像的边缘以及图像角点等特征信息。
It is our aim to denoise and preserve the details such as edges and corners in the image as much as possible.
但是中值滤波去除椒盐噪声时有其同有缺点，比如说中值滤波并不能很好地保持边缘以及图像中的大量细节信息，所以中值滤波在对边缘和细节要求严格的情况下并不能带来很好的处理效果。
But median filter can not preserving edges and most details of images, so median filter is not able to produce a satisfying result especially when edges and details are strictly requested to preserve.
实验结果表明此方法是可行的，既减少了分水岭变换的过分割现象，又较好地保持了图像中的边缘信息，能得到良好的分割效果。
The experimental results show that the proposed method is feasible and can give better image segmentation. It does not only avoid the over-segmentation, but also preserves the edge information.
结构张量包含有图像的邻域结构特征，借助这些信息可在降噪的同时保持图像边缘的细节特征。
The structure tensor contains neighborhood structure features of image. It can preserve the details of images edge as well as image de-noising.
结构张量包含有图像的邻域结构特征，借助这些信息可在降噪的同时保持图像边缘的细节特征。
The structure tensor contains neighborhood structure features of image. It can preserve the details of images edge as well as image de-noising.
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