Title
Weighted aggregation for guided image filtering
Abstract
As a local filter, the guided image filtering (GIF) suffers from halo artifacts. To address this issue, a novel weighted aggregating strategy is proposed in this paper. By introducing the weighted aggregation to GIF, the proposed method called WAGIF can achieve results with sharp edges and avoid/reduce halo artifacts. More specifically, compared to the weighted guided image filtering and the gradient domain guided image filtering, the proposed method can achieve both fine and coarse smoothing results in the flat areas while preserving edges. In addition, the complexity of the proposed approach is O(N) for an image with N pixels. It is demonstrated that the GIF with weighted aggregation performs well in the fields of computational photography and image processing, including single image detail enhancement, tone mapping of high-dynamic-range images, single image haze removal, etc.
Year
DOI
Venue
2020
10.1007/s11760-019-01579-1
Signal, Image and Video Processing
Keywords
DocType
Volume
Edge-preserving filtering, Weighted aggregation, Detail enhancement, HDR tone mapping, Haze removal
Journal
14
Issue
ISSN
Citations 
3
1863-1703
1
PageRank 
References 
Authors
0.35
0
2
Name
Order
Citations
PageRank
Bin Chen110.69
Shiqian Wu2134785.75