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Research Article | Open Access

Least-squares images for edge-preserving smoothing

Hui Wang1, Junjie Cao2, Xiuping Liu2( ), Jianmin Wang1, Tongrang Fan1, Jianping Hu3
School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang 050043, China.
School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China.
School of Sciences, Northeast Dianli University, Jilin 132012, China.
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Abstract

In this paper, we propose least-squares images (LS-images) as a basis for a novel edge-preserving image smoothing method. The LS-image requires the value of each pixel to be a convex linear combination of its neighbors, i.e., to have zero Laplacian, and to approximate the original image in a least-squares sense. The edge-preserving property inherits from the edge-aware weights for constructing the linear combination. Experimental results demonstrate that the proposed method achieves high quality results compared to previous state-of-the-art works. We also show diverse applications of LS-images, such as detail manipulation, edge enhancement, and clip-art JPEG artifact removal.

Keywords

image enhancementfeature-preservingimage smoothingleast-squares images (LS-images)

References

[1]
Perona, P.; Malik, J. Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 12, No. 7, 629-639, 1990.
Crossref Google Scholar
[2]
Rudin, L. I.; Osher, S.; Fatemi, E. Nonlinear total variation based noise removal algorithms. Physica D: Nonlinear Phenomena Vol. 60, Nos. 1–4, 259-268, 1992.
Crossref Google Scholar
[3]
Tomasi, C.; Manduchi, R. Bilateral filtering for gray and color images. In: Sixth International Conference on Computer Vision, 839-846, 1998.
[4]
Comaniciu, D.; Meer, P. Mean shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 24, No. 5, 603-619, 2002.
Crossref Google Scholar
[5]
Farbman, Z.; Fattal, R.; Lischinski, D.; Szeliski, R. Edge-preserving decompositions for multi-scale tone and detail manipulation. ACM Transactions on Graphics Vol. 27, No. 3, Article No. 67, 2008.
Crossref Google Scholar
[6]
Subr, K.; Soler, C.; Durand, F. Edge-preserving multiscale image decomposition based on local extrema. ACM Transactions on Graphics Vol. 28, No. 5, Article No. 147, 2009.
Crossref Google Scholar
[7]
Fattal, R. Edge-avoiding wavelets and their applications. ACM Transactions on Graphics Vol. 28, No. 3, Article No. 22, 2009.
Crossref Google Scholar
[8]
Farbman, Z.; Fattal, R.; Lischinski, D. Diffusion maps for edge-aware image editing. ACM Transactions on Graphics Vol. 29, No. 6, Article No. 145, 2010.
Crossref Google Scholar
[9]
Xu, L.; Lu, C.; Xu, Y.; Jia, J. Image smoothing via L0 gradient minimization. ACM Transactions on Graphics Vol. 30, No. 6, Article No. 174, 2011.
Crossref Google Scholar
[10]
Paris, S.; Hasinoff, S. W.; Kautz, J. Local Laplacian filters: Edge-aware image processing with a Laplacian pyramid. ACM Transactions on Graphics Vol. 30, No. 4, Article No. 68, 2011.
Crossref Google Scholar
[11]
He, K.; Sun, J.; Tang, X. Guided image filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 35, No. 6, 1397-1409, 2013.
Crossref Google Scholar
[12]
Cheng, X.; Zeng, M.; Liu, X. Feature-preserving filtering withL0 gradient minimization. Computers & Graphics Vol. 38, 150-157, 2014.
Crossref Google Scholar
[13]
Levin, A.; Lischinski, D.; Weiss, Y. Colorization using optimization. ACM Transactions on Graphics Vol. 23, No. 3, 689-694, 2004.
Crossref Google Scholar
[14]
Grady, L. Random walks for image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 28, No. 11, 1768-1783, 2006.
Crossref Google Scholar
[15]
Sorkine, O.; Cohen-Or, D. Least-squares meshes. In: Proceedings of the Shape Modeling International, 191-199, 2004.
[16]
Sorkine, O. Differential representations for mesh processing. Computer Graphics Forum Vol. 25, No. 4, 789-807, 2006.
Crossref Google Scholar
[17]
Sorkine, O.; Cohen-Or, D.; Irony, D.; Toledo, S. Geometry-aware bases for shape approximation. IEEE Transactions on Visualization and Computer Graphics Vol. 11, No. 2, 171-180, 2005.
Crossref Google Scholar
[18]
Chen, D.; Cohen-Or, D.; Sorkine, O.; Toledo, S. Algebraic analysis of high-pass quantization. ACM Transactions on Graphics Vol. 24, No. 4, 1259-1282, 2005.
Crossref Google Scholar
[19]
Chen, J.; Paris, S.; Durand, F. Real-time edge-aware image processing with the bilateral grid. ACM Transactions on Graphics Vol. 26, No. 3, Article No. 103, 2007.
Crossref Google Scholar
[20]
Yang, Q.; Tan, K.-H.; Ahuja, N. Real-time O(1) bilateral filtering. In: IEEE Conference on Computer Vision and Pattern Recognition, 557-564, 2009.
Crossref
[21]
Gastal, E. S. L.; Oliveira, M. M. Adaptive manifolds for real-time high-dimensional filtering. ACM Transactions on Graphics Vol. 31, No. 4, Article No. 33, 2012.
Crossref Google Scholar
[22]
Cho, H.; Lee, H.; Kang, H.; Lee, S. Bilateral texture filtering. ACM Transactions on Graphics Vol. 33, No. 4, Article No. 128, 2014.
Crossref Google Scholar
[23]
Criminisi, A.; Sharp, T.; Rother, C.; Pérez, P. Geodesic image and video editing. ACM Transactions on Graphics Vol. 29, No. 5, Article No. 134, 2010.
Crossref Google Scholar
[24]
Gastal, E. S. L.; Oliveiral, M. M. Domain transform for edge-aware image and video processing. ACM Transactions on Graphics Vol. 30, No. 4, Article No. 69, 2011.
Crossref Google Scholar
[25]
Karacan, L.; Erdem, E.; Erdem, A. Structure-preserving image smoothing via region covariances. ACM Transactions on Graphics Vol. 32, No. 6, Article No. 176, 2013.
Crossref Google Scholar
[26]
Huang, S.-S.; Zhang, G.-X.; Lai, Y.-K.; Kopf, J.; Cohen-Or, D.; Hu, S.-M. Parametric meta-filter modeling from a single example pair. The Visual Computer Vol. 30, Nos. 6–8, 673-684, 2014.
Crossref Google Scholar
[27]
Xu, L.; Yan, Q.; Xia, Y.; Jia, J. Structure extraction from texture via relative total variation. ACM Transactions on Graphics Vol. 31, No. 6, Article No. 139, 2012.
Crossref Google Scholar
[28]
Li, X.-Y.; Gu, Y.; Hu, S.-M.; Martin, R. R. Mixed-domain edge-aware image manipulation. IEEE Transactions on Image Processing Vol. 22, No. 5, 1915-1925, 2013.
Crossref Google Scholar
[29]
Zang, Y.; Huang, H.; Zhang, L. Efficient structure-aware image smoothing by local extrema on space-filling curve. IEEE Transactions on Visualization and Computer Graphics Vol. 20, No. 9, 1253-1265, 2014.
Crossref Google Scholar
[30]
Zhang, S.-H.; Li, X.-Y.; Hu, S.-M.; Martin, R. R. Online video stream abstraction and stylization. IEEE Transactions on Multimedia Vol. 13, No. 6, 1286-1294, 2011.
Crossref Google Scholar
[31]
Kyprianidis, J. E.; Kang, H. Image and video abstraction by coherence-enhancing filtering. Computer Graphics Forum Vol. 30, No. 2, 593-602, 2011.
Crossref Google Scholar
[32]
Botsch, M.; Sorkine, O. On linear variational surface deformation methods. IEEE Transactions on Visualization and Computer Graphics Vol. 14, No. 1, 213-230, 2008.
Crossref Google Scholar
Computational Visual Media
Volume 1 Issue 1,
March 2015
Pages 27-35
DOI: 10.1007/s41095-015-0004-6
Cite this article:
Wang H, Cao J, Liu X, et al. Least-squares images for edge-preserving smoothing. Computational Visual Media, 2015, 1(1): 27-35. https://doi.org/10.1007/s41095-015-0004-6

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Revised: 26 September 2014
Accepted: 19 January 2015
Published: 08 August 2015
© The Author(s) 2015

This article is published with open access at Springerlink.com

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
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