Abstract
In this paper, we propose a novel texture filtering method. Starting with a texture boundary extraction, we obtain the possibility of texture boundary with the statistics of the proportion of the pixels in different colors. The possibility of texture boundary can be obtained by calculating the Bhattacharyya distance of the color proportion on each side of each pixel. Further, we build a filtering scale map to guide the parameters of the filter. This filtering scale map is based on the texture boundary. Finally, to obtain the texture filtering result, we design an adaptive shape edge-preserving filter which is simple and effective. By counting the color information of all pixel neighborhoods the filter can select the pixels in a similar color to filter. Experiments are performed on different color-texture images, and the results show that our proposed method performs much better compared with state-of-the-art methods on texture filtering.
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Our raw data all come from experiments, which are reliable and available. The key data generated or analyzed during this study are included in the submitted article.
Abbreviations
- WLS:
-
weighted least squares
- RTV:
-
relative total variation
- STF:
-
subsequent texture filtering
- RGF:
-
Rolling Guidance Filter
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Acknowledgements
We acknowledge Jilin University who provides instruments and experimental sites. We are grateful for that Southern Marine Science and Engineering Guangdong Laboratory provides funds.
Funding
This research was funded by National Natural Science Foundation of China (41827803) and Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang) (ZJW-2019-04).
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The research and the outcome of this specific publication are the result of a long cooperation between the authors about the development and applications of the vibroseis and geophones. All authors read and approved the final manuscript.
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Li, X., Li, L., Gao, Y. et al. Texture filtering with filtering scale map. Multidim Syst Sign Process 33, 1105–1117 (2022). https://doi.org/10.1007/s11045-022-00833-z
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DOI: https://doi.org/10.1007/s11045-022-00833-z