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Linear Recursive Non-Local Edge-Aware Filter
IEEE Transactions on Circuits and Systems for Video Technology ( IF 8.4 ) Pub Date : 2020-08-11 , DOI: 10.1109/tcsvt.2020.3015840
Penghui Bu , Hong Zhao , Yusheng Jin , Yueyang Ma

It is challenging to extend the support region of state-of-the-art local edge-preserving filtering approaches to the entire input image on account of huge memory cost and heavy computational burden. In this paper, we propose an $O(N)$ time recursive non-local edge-aware filter. A novel graph and a linear time algorithm are presented to effectively propagate information across the entire image. In this graph, information is propagated along all directions to avoid visual artifacts. Both the intensity similarity and the spatial affinity are utilized to estimate the similarity of neighboring pixels, and the distance of any two pixels is the length of the path between these two pixels on a binary tree. Specifically, the input image is filtered at four directions, namely left-to-right, right-to-left, top-to-bottom and bottom-to-top. In each pass, the un-normalized output and the normalization constant of the root node are computed recursively from leaf nodes to the root node on a binary tree in linear time. The filtering output is the average of the outputs for these four directions. A comparison with other non-local edge-aware filters is presented to show the advantages of our approach. Extensive experiments demonstrate that our recursive non-local edge-preserving filter is effective in a variety of computer vision and image processing applications, including edge-aware filtering, detail enhancement, stylization, and stereo matching.

中文翻译:

线性递归非局部边缘感知滤波器

由于巨大的存储成本和沉重的计算负担,将现有技术的局部边缘保留滤波方法的支持区域扩展到整个输入图像具有挑战性。在本文中,我们提出了 $ O(N)$ 时间递归非本地边缘感知过滤器。提出了一种新颖的图形和一个线性时间算法来有效地在整个图像上传播信息。在此图中,信息沿所有方向传播,以避免视觉伪影。强度相似度和空间相似度都用于估计相邻像素的相似度,任何两个像素的距离就是二叉树上这两个像素之间路径的长度。具体地,在四个方向上对输入图像进行滤波,即从左到右,从右到左,从上到下和从下到上。在每遍中,在线性时间内从叶节点到二叉树上的根节点递归计算根节点的未归一化输出和归一化常数。滤波输出是这四个方向的平均输出。提出了与其他非本地边缘感知过滤器的比较,以显示我们方法的优势。大量实验表明,我们的递归非局部边缘保留滤镜在各种计算机视觉和图像处理应用中均有效,包括边缘感知滤镜,细节增强,样式化和立体匹配。
更新日期:2020-08-11
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