Multi-scale structure-preserving image filtering
Edge-preserving filtering is vital in many image processing and computer vision tasks. However, existing techniques, such as the bilateral filter and the guided filter, have limitations when dealing with stronger filtering strengths, resulting in the suppression of image structures. In this work, we...
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| Main Authors: | , |
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| Format: | text |
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Animo Repository
2017
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| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2191 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3190/type/native/viewcontent |
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| Institution: | De La Salle University |
| Summary: | Edge-preserving filtering is vital in many image processing and computer vision tasks. However, existing techniques, such as the bilateral filter and the guided filter, have limitations when dealing with stronger filtering strengths, resulting in the suppression of image structures. In this work, we discuss an alternative structure-preserving image filter (SPIF) that operates on multiple detail densities (i.e. scales) so as to overcome the trade-off between filtering strength and edge-preservation. We show, using several experiments, that the proposed filter is capable of performing various tasks, specifically detail enhancement and image abstraction, while maintaining low computational times. The parameterization of the proposed filter provides a high degree of flexibility, allowing it to perform well for the aforementioned tasks, and potentially, in many other tasks. © 2017 IEEE. |
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