Interpreting and Extending the Guided Filter via Cyclic Coordinate Descent

The guided filter (GF) is a widely used smoothing tool in computer vision and image processing. However, to the best of our knowledge, few papers investigate the mathematical connection between this filter and the least-squares optimization. In this paper, we first interpret the guided filter as the...

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Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 28(2019), 2 vom: 12. Feb., Seite 767-778
1. Verfasser: Dai, Longquan (VerfasserIn)
Weitere Verfasser: Yuan, Mengke, Tang, Liang, Xie, Yuan, Zhang, Xiaopeng, Tang, Jinhui
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2019
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article
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520 |a The guided filter (GF) is a widely used smoothing tool in computer vision and image processing. However, to the best of our knowledge, few papers investigate the mathematical connection between this filter and the least-squares optimization. In this paper, we first interpret the guided filter as the cyclic coordinate descent (CCD) solver of a least-squares objective function. This discovery implies an extension approach to generalize the guided filter since we can change the least-squares objective function and define new filters as the first pass iteration of the CCD solver of modified objective functions. In addition, referring to the iterative minimizing procedure of the CCD, we can derive new rolling filtering schemes. So, we are reasonable to say that our discovery not only reveals an approach to design new GF-like filters adapting to specific requirements of applications but also offers thorough explanations for two rolling filtering schemes of the guided filter as well as the method to extend them. Experiments prove our new proposed filters and rolling filtering schemes could produce state-of-the-art results 
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700 1 |a Yuan, Mengke  |e verfasserin  |4 aut 
700 1 |a Tang, Liang  |e verfasserin  |4 aut 
700 1 |a Xie, Yuan  |e verfasserin  |4 aut 
700 1 |a Zhang, Xiaopeng  |e verfasserin  |4 aut 
700 1 |a Tang, Jinhui  |e verfasserin  |4 aut 
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