There is typically a trade-off between removing the detailed appearance (i.e., geometric textures) and preserving the intrinsic properties (i.e., geometric structures) of 3D surfaces. The conventional use of mesh vertex/facet-centered patches in many filters leads to side-effects including remnant textures, improperly filtered structures, and distorted shapes. We propose a selective guidance normal filter (SGNF) which adapts the Relative Total Variation (RTV) to a maximal/minimal scheme (mmRTV). The mmRTV measures the geometric flatness of surface patches, which helps in finding adaptive patches whose boundaries are aligned with the facet being processed. The adaptive patches provide selective guidance normals, which are subsequently used for normal filtering. The filtering smooths out the geometric textures by using guidance normals estimated from patches with maximal RTV (the least flatness), and preserves the geometric structures by using normals estimated from patches with minimal RTV (the most flatness). This simple yet effective modification of the RTV makes our SGNF specialized rather than trade off between texture removal and structure preservation, which is distinct from existing mesh filters. Experiments show that our approach is visually and numerically comparable to the state-of-the-art mesh filters, in most cases. In addition, the mmRTV is generally applicable to bas-relief modeling and image texture removal.

中文翻译：

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用于几何纹理去除的选择性引导法线过滤器。

在去除细节外观（即几何纹理）和保留 3D 表面的内在属性（即几何结构）之间通常需要进行权衡。在许多过滤器中传统使用网格顶点/以面为中心的补丁会导致副作用，包括残余纹理、过滤不当的结构和扭曲的形状。我们提出了一种选择性引导法向滤波器 (SGNF)，它使相对总变异 (RTV) 适应最大/最小方案 (mmRTV)。mmRTV 测量表面补丁的几何平面度，这有助于找到边界与正在处理的面对齐的自适应补丁。自适应补丁提供选择性引导法线，随后用于法线过滤。过滤通过使用从具有最大 RTV（最不平坦度）的块估计的引导法线来平滑几何纹理，并通过使用从具有最小 RTV（最平坦度）的块估计的法线来保留几何结构。RTV 的这种简单而有效的修改使我们的 SGNF 专门化，而不是在纹理去除和结构保留之间进行权衡，这与现有的网格过滤器不同。实验表明，在大多数情况下，我们的方法在视觉上和数值上与最先进的网状过滤器相当。此外，mmRTV 一般适用于浅浮雕建模和图像纹理去除。RTV 的这种简单而有效的修改使我们的 SGNF 专门化，而不是在纹理去除和结构保留之间进行权衡，这与现有的网格过滤器不同。实验表明，在大多数情况下，我们的方法在视觉上和数值上与最先进的网状过滤器相当。此外，mmRTV 一般适用于浅浮雕建模和图像纹理去除。这种简单而有效的 RTV 修改使我们的 SGNF 专门化，而不是在纹理去除和结构保留之间进行权衡，这与现有的网格过滤器不同。实验表明，在大多数情况下，我们的方法在视觉上和数值上与最先进的网状过滤器相当。此外，mmRTV 一般适用于浅浮雕建模和图像纹理去除。