Anisotropic Guided Filtering
Anisotropic Guided Filtering
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DOI：
10.1109/tip.2019.2941326
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发表时间：
2020-01-01
影响因子：
10.6
通讯作者：
Yamashita, Yukihiko
中科院分区：
文献类型：
--
作者：
Ochotorena, Carlo Noel;Yamashita, Yukihiko
引导滤波器及其后续衍生物已被广泛应用于许多图像处理和计算机视觉应用中，主要是由于其低复杂度和良好的边缘保护特性。尽管取得了这一成功，但引导滤波器的不同变体无法处理更积极的滤波强度，从而导致“细节晕圈”的表现。同时，当输入图像和引导图像具有结构不一致性时，这些现有的滤波器表现不佳。在本文中，我们证明了这些限制是由于引导过滤器作为一个可变强度的局部各向同性过滤器，在效果上，作为一个弱的各向异性过滤器的图像。我们的分析表明，这种行为源于在引导滤波器变体的最后步骤中使用未加权平均，包括自适应引导滤波器（AGF），加权引导图像滤波器（WGIF）和梯度域引导图像滤波器（GGIF）。我们提出了一种新的过滤器，各向异性导向过滤器（AnisGF），利用加权平均，以实现最大的扩散，同时保持强边缘的图像。所提出的权重基于局部邻域方差进行优化，以实现强各向异性滤波，同时保持原始引导滤波器的低计算成本。合成测试表明，所提出的方法解决了存在的细节晕和处理不一致的结构中发现以前的变体的引导过滤器。此外，在尺度感知滤波，细节增强，纹理去除，和色度上采样实验证明了该技术带来的改善。
The guided filter and its subsequent derivatives have been widely employed in many image processing and computer vision applications primarily brought about by their low complexity and good edge-preservation properties. Despite this success, the different variants of the guided filter are unable to handle more aggressive filtering strengths leading to the manifestation of "detail halos". At the same time, these existing filters perform poorly when the input and guide images have structural inconsistencies. In this paper, we demonstrate that these limitations are due to the guided filter operating as a variable-strength locally-isotropic filter that, in effect, acts as a weak anisotropic filter on the image. Our analysis shows that this behaviour stems from the use of unweighted averaging in the final steps of guided filter variants including the adaptive guided filter (AGF), weighted guided image filter (WGIF), and gradient-domain guided image filter (GGIF). We propose a novel filter, the Anisotropic Guided Filter (AnisGF), that utilises weighted averaging to achieve maximum diffusion while preserving strong edges in the image. The proposed weights are optimised based on the local neighbourhood variances to achieve strong anisotropic filtering while preserving the low computational cost of the original guided filter. Synthetic tests show that the proposed method addresses the presence of detail halos and the handling of inconsistent structures found in previous variants of the guided filter. Furthermore, experiments in scale-aware filtering, detail enhancement, texture removal, and chroma upsampling demonstrate the improvements brought about by the technique.