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.
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Hui Wang is a lecturer in School of Information Science and Technology at Shijiazhuang Tiedao University, China. He received the Ph.D. degree in computational mathematics at Dalian University of Technology in 2013. His research interests include computer graphics, digital geometry processing, and image processing.
Junjie Cao is a lecturer in School of Mathematical Sciences at Dalian University of Technology, China. He received the Ph.D. degree in computational mathematics from Dalian University of Technology. His research interests include shape modeling, image processing, and machine learning.
Xiuping Liu is a professor in School of Mathematical Sciences at Dalian University of Technology, China. She received the Ph.D. degree in computational mathematics from Dalian University of Technology. Her research interests include shape modeling and analysis.
Jianmin Wang is an associate professor in School of Information Science and Technology at Shijiazhuang Tiedao University, China. His current research interests include software engineering and network technology.
Tongrang Fan is a professor in School of Information Science and Technology at Shijiazhuang Tiedao University, China. Her current research interests include network technology, network security technology, and intelligent information processing.
Jianping Hu is an associate professor in College of Sciences at Northeast Dianli University, China. He obtained his B.S. and M.S. degrees in mathematics at Jilin University. He received his Ph.D. degree in computational mathematics at Dalian University of Technology in 2009. His research interests include computer graphics, computational geometry, and image processing.
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Wang, H., Cao, J., Liu, X. et al. Least-squares images for edge-preserving smoothing. Comp. Visual Media 1, 27–35 (2015). https://doi.org/10.1007/s41095-015-0004-6
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DOI: https://doi.org/10.1007/s41095-015-0004-6