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Pyramid Texture Filtering
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AI
DOI：10.1145/3592120.png)
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Abstract
En 中文
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. Code is available at https://rewindl.github.io/pyramid_texture_filtering/.
Keywords:
image smoothing
structure extraction
image decomposition
image pyramid
upsampling
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