Multi-scale guided filtering integrated with superpixel and patch shift

Jianwu LONG; Jiangzhou ZHU

doi:10.11959/j.issn.1000-436x.2022220

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Multi-scale guided filtering integrated with superpixel and patch shift

Papers | 更新时间：2024-06-05

- Multi-scale guided filtering integrated with superpixel and patch shift
- Journal on Communications Vol. 43, Issue 11, Pages: 158-170(2022)
- 作者机构：
  
  重庆理工大学计算机科学与工程学院，重庆 400054
- 作者简介：
- 基金信息：
  
  Young Scientists Project of Science and Technology Research Program of Chongqing Education Commission of China(KJQN202201148);The National Natural Science Foundation of China for Young Scientists(61502065);Foundation and Frontier Research Key Program of Chongqing Science and Technology Commission(cstc2015jcyjBX0127);Humanities and Social Sciences Research Key Program of Chongqing Municipal Education Commission(17SKG136);Graduate Innovation Project of Chongqing University of Technology(clgycx20202096)
- DOI：10.11959/j.issn.1000-436x.2022220
  CLC： TP391
- Online First：2022-11，
  
  Published：25 November 2022
- 稿件说明：
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Jianwu LONG, Jiangzhou ZHU. Multi-scale guided filtering integrated with superpixel and patch shift[J]. Journal on Communications, 2022, 43(11): 158-170.
DOI：

Jianwu LONG, Jiangzhou ZHU. Multi-scale guided filtering integrated with superpixel and patch shift[J]. Journal on Communications, 2022, 43(11): 158-170. DOI： 10.11959/j.issn.1000-436x.2022220.

摘要

为避免边缘在滤波时容易出现模糊的现象，提出融合超像素与窗口偏移的多尺度引导滤波。首先，对图像进行双边滤波以得到更加准确的超像素区域；然后，通过窗口偏移的度量函数选择尽可能不包含边缘信息的局部窗口，取与当前像素所在超像素区域的重叠部分作为最终滤波区域；最后，使用小尺度窗口保留边缘，再增大窗口尺度进行迭代引导滤波，融合不同尺度窗口的滤波结果得到最终的滤波输出，实现平滑细节的同时保留结构边缘。此外，提出更适用于滤波结果质量评价的指标并在不同算法中进行对比，所提算法有着更强的边缘保留能力，能获得比其他算法更佳的滤波效果。

Abstract

In order to avoid the phenomenon that edges were easily blurred during filtering

a multi-scale guided filtering integrated with superpixel and patch shift was proposed.Firstly

the bilateral filtering was applied to an input image to get more accurate superpixel regions.Then

the overlapping was used as the final filtering region

which was formed by the local window and the superpixel.The local window was selected by a metric function so that it did not contain edge information as much as possible.Finally

a small-scale window was used to preserve the edges

and then the window scale was increased for iterative guided filtering.The final filtering output was calculated by fusing the results of different window scales to smooth details while preserving the structural edges.Additionally

the evaluation index of filtering results quality was proposed and compared in different algorithms.The proposed algorithm has stronger edge preservation ability and can obtain better filtering effectiveness than other algorithms.

关键词

Keywords

references

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