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Weighted Guided Image Filtering – A Survey

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Nidhi Sen, Akhilesh Jain, Swapnil Jain

Nidhi Sen, Akhilesh Jain and Swapnil Jain. Weighted Guided Image Filtering – A Survey. International Journal of Computer Applications 156(10):29-32, December 2016. BibTeX

	author = {Nidhi Sen and Akhilesh Jain and Swapnil Jain},
	title = {Weighted Guided Image Filtering – A Survey},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {156},
	number = {10},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {29-32},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2016912541},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


It is well-known that local filtering-based edge preserving smoothing method suffers from halo artifacts. In this paper, a weighted guided image filter is introduced by incorporating an edge-aware weighting into an accessible guided image filter to address the problem. The WGIF inherit benefits of both global and local smoothing filters in the sense that: 1) the difficulty of the WGIF is O(N) for an image with N pixels, which is same as the GIF and 2) the WGIF can avoid halo artifact like the existing global smoothing filters. The WGIF is applied for single image detail enhancement, single image mist removal, and fusion of differently exposed images. Investigational results show that the resultant algorithms create images with better visual quality and at the same time halo artifacts can be avoided from appearing in the final images with negligible rise on running times.


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Edge-preserving smoothing, weighted guided image filter, edge-aware weighting, detail enhancement, haze removal, exposure fusion .