An Efficient and Scalable Image Filtering Framework Using VIPS Fusion

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Date
2013
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Journal ISSN
Volume Title
Publisher
The Eurographics Association and Blackwell Publishing Ltd.
Abstract
Edge-preserving image filtering is a valuable tool for a variety of applications in image processing and computer vision. Motivated by a new simple but effective local Laplacian filter, we propose a scalable and efficient image filtering framework to extend this edge-preserving image filter and construct an uniform implementation in O(N) time. The proposed framework is built upon a practical global-to-local strategy. The input image is first remapped globally by a series of tentative remapping functions to generate a virtual candidate image sequence (Virtual Image Pyramid Sequence, VIPS). This sequence is then recombined locally to a single output image by a flexible edge-aware pixel-level fusion rule. To avoid halo artifacts, both the output image and the virtual candidate image sequence are transformed into multi-resolution pyramid representations. Four examples, single image de-hazing, multi-exposure fusion, fast edge-preserving filtering and tone-mapping, are presented as the concrete applications of the proposed framework. Experiments on filtering effect and computational efficiency indicate that the proposed framework is able to build a wide range of fast image filtering that yields visually compelling results.
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@article{
:10.1111/cgf.12247
, journal = {Computer Graphics Forum}, title = {{
An Efficient and Scalable Image Filtering Framework Using VIPS Fusion
}}, author = {
Zhang, Jun
and
Chen, Xiuhong
and
Zhao, Yan
and
Li, H.
}, year = {
2013
}, publisher = {
The Eurographics Association and Blackwell Publishing Ltd.
}, ISSN = {
1467-8659
}, DOI = {
/10.1111/cgf.12247
} }
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