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Edge guidance filtering for structure extraction

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Abstract

Smoothing the multiscale, irregular, and high contrast textures while maintaining structures with small details is challenging for the existing texture filtering methods. In this paper, we put forward a novel edge guidance-based texture filter with an adaptive kernel scale scheme to address these challenges. The texture edges are identified by a texture edge detector first. Then, based on the texture edges, a variable per-pixel smoothing scale is selected to construct the scale map, which is used to guide the filtering. In the end, a novel pixel-selected filter is designed as post-processing to optimize the filtered images. The experimental results compared with the state-of-the-art methods show that our method has a better performance in suppressing different forms of textures while maintaining the main structure. In addition, our method can be applied well in a variety of image processing applications including: detail enhancement, inverse halftoning, virtual contour restoration and texture image segmentation.

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Acknowledgements

This work was supported by China’s national major scientific research instrument development project (42127807), Key project of Guangdong Province for Promoting High-quality Economic Development (Marine Economic Development) in 2022: Research and development of key technology and equipment for Marine vibroseis system (GDNRC[2022]29), Special fund for applied basic research of Changchun Science and Technology Department(21ZY21), Jilin Science and technology development plan, key R & D projects (20220201055GX), and Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang) under contract No.ZJW-2019-04.

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Correspondence to Yang Liu.

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Sun, B., Qi, Y., Zhang, G. et al. Edge guidance filtering for structure extraction. Vis Comput 39, 5327–5342 (2023). https://doi.org/10.1007/s00371-022-02662-4

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