We present a simple but effective technique to smooth out textures while preserving the prominent structures. Our method is built upon a key observation -- the coarsest level in a Gaussian pyramid often naturally eliminates textures and summarizes the main image structures. This inspires our central idea for texture filtering, which is to progressively upsample the very low-resolution coarsest Gaussian pyramid level to a full-resolution texture smoothing result with well-preserved structures, under the guidance of each fine-scale Gaussian pyramid level and its associated Laplacian pyramid level. We show that our approach is effective to separate structure from texture of different scales, local contrasts, and forms, without degrading structures or introducing visual artifacts. We also demonstrate the applicability of our method on various applications including detail enhancement, image abstraction, HDR tone mapping, inverse halftoning, and LDR image enhancement.

翻译：我们提出一种简单而有效的技术，可在保持显著结构的同时平滑纹理。该方法基于一个关键观察——高斯金字塔中的最粗层级通常能自然消除纹理并概括图像主要结构。这启发我们纹理滤波的核心思想：在各精细尺度高斯金字塔层级及其对应拉普拉斯金字塔层级的引导下，逐步将极低分辨率的最粗高斯金字塔层级上采样至全分辨率且保持结构完好的纹理平滑结果。研究表明，该方法能有效分离不同尺度、局部对比度及形态的纹理与结构，且不破坏结构或引入视觉伪影。我们还展示了该方法在细节增强、图像抽象化、HDR色调映射、逆半色调化及低动态范围图像增强等多种应用中的适用性。