Multi-scale structure-preserving image filtering
College
Gokongwei College of Engineering
Department/Unit
Electronics And Communications Engg
Document Type
Conference Proceeding
Source Title
2017 IEEE 19th International Workshop on Multimedia Signal Processing, MMSP 2017
Volume
2017-January
First Page
1
Last Page
6
Publication Date
11-27-2017
Abstract
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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Digitial Object Identifier (DOI)
10.1109/MMSP.2017.8122290
Recommended Citation
Ochotorena, C., & Yamashita, Y. (2017). Multi-scale structure-preserving image filtering. 2017 IEEE 19th International Workshop on Multimedia Signal Processing, MMSP 2017, 2017-January, 1-6. https://doi.org/10.1109/MMSP.2017.8122290
Disciplines
Electrical and Computer Engineering
Keywords
Image processing; Computer vision
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