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Partial Ellipse Filter for Maximizing Region Similarity for Noise Removal and Color Regulation

机译:局部椭圆滤波器可最大化区域相似度,以实现去噪和色彩调节

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Ellipse filters can be implemented for partition of image patch. We introduce a method for automatically obtaining a set of neighbor patches for an image pixel in form of ellipses for noise removal and color regulation. Comparing neighborhood similarity of patches of the set allows selecting an optimal patch. The evaluation of similarity is developed from bilateral filter with additional orientation condition. Through the development of the image filter model it is shown that the image noise can be removed better with the ellipse patches that are allocated in different directions. Our first finding is that it is enough to select 4 or 8 major orientations to determine the best ellipse patch for each pixel. Secondly, by operating convolution weighted by intensity similarity and the spatial distance, this is capable to detect particular oriented patch with the best neighbor similarity and ameliorate the elimination of different noise types. These filters also permit remaining color harmony and edge contrast for color correction. In particular, the validity of the method is demonstrated by presenting experimental results on a benchmark database.
机译:椭圆过滤器可以实现图像斑块的分区。我们介绍了一种方法,该方法可以自动获取椭圆形的图像像素的一组相邻像素块,以进行噪声去除和颜色调节。比较集合的补丁的邻域相似性允许选择最佳补丁。相似性评估是从带有附加定向条件的双边滤波器中开发出来的。通过图像滤波器模型的开发,表明使用在不同方向分配的椭圆形色块可以更好地消除图像噪声。我们的第一个发现是选择4个或8个主要方向来确定每个像素的最佳椭圆斑块就足够了。其次,通过对以强度相似度和空间距离加权的卷积进行运算,这能够检测到具有最佳邻域相似度的特定定向面片,并改善消除不同噪声类型的能力。这些滤光片还允许保留色彩和谐度和边缘对比度,以进行色彩校正。特别地,通过在基准数据库上呈现实验结果证明了该方法的有效性。

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