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Regular Paper

Image Smoothing Based on Image Decomposition and Sparse High Frequency Gradient

School of Computer Science and Technology, Shandong University, Jinan 250101, China
Shandong Co-Innovation Center of Future Intelligent Computing, Yantai 264025, China
School of Software, Shandong University, Jinan 250101, China
Digital Media Research Institute, Shandong University of Finance and Economics, Jinan 250061, China
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Abstract

Image smoothing is a crucial image processing topic and has wide applications. For images with rich texture, most of the existing image smoothing methods are difficult to obtain significant texture removal performance because texture containing obvious edges and large gradient changes is easy to be preserved as the main edges. In this paper, we propose a novel framework (DSHFG) for image smoothing combined with the constraint of sparse high frequency gradient for texture images. First, we decompose the image into two components: a smooth component (constant component) and a non-smooth (high frequency) component. Second, we remove the non-smooth component containing high frequency gradient and smooth the other component combining with the constraint of sparse high frequency gradient. Experimental results demonstrate the proposed method is more competitive on efficiently texture removing than the state-of-the-art methods. What is more, our approach has a variety of applications including edge detection, detail magnification, image abstraction, and image composition.

Keywords

image smoothingtexture removalimage decomposition

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Journal of Computer Science and Technology
Volume 33 Issue 3,
May 2018
Pages 502-510
DOI: 10.1007/s11390-018-1834-3
Cite this article:
Ma G-H, Zhang M-L, Li X-M, et al. Image Smoothing Based on Image Decomposition and Sparse High Frequency Gradient. Journal of Computer Science and Technology, 2018, 33(3): 502-510. https://doi.org/10.1007/s11390-018-1834-3

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Received: 05 January 2018
Accepted: 30 March 2018
Published: 11 May 2018
©2018 LLC & Science Press, China
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